DBaaS E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registery API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation Database Management in E2E Networks DBaaS DBaaS Introduction E2Es DBaaS provides a selection of node types optimized to fit different relational database use cases consisting of different database engines Node Cluster configuration comprises varying combinations of CPU memory storage and gives you the flexibility to choose the appropriate mix of resources for your database E2Es Relational DBaaS Service makes it easier for us to set up and operate Relational Databases in the cloud providing us with Costefficient service and automating timeconsuming administrator tasks such as Provisioning Patching and Setups Benefits Easy Administration Database makes it easier to deploy the nodes Using the Myaccount portal with just a click away from providing necessary details you will be able to provision the node There will not be any administrative task of installing or maintaining the database software Scalability and Failover Database with only a few clicks helps you setup a slave which allows you to launch one or more Read Replicas to offload read traffic from your primary database nodes Speed Database Supports the most demanding application You can choose between different cluster configurations based on your usage which are optimized for high performance Secure Database is highly secure restricting access to the external environment with Firewall It Provides the necessary option for you to optimize the setting so that only a known and existing host will be able to connect with your database Getting Started with Database E2Es DBaaS is a service that makes it easier to set up operate and scale a relational database in the cloud MyAccount Portal provides you a webbased interface for accessing and managing all your Database resources How to Create a Database Cluster in Myaccount Portal This section will show you how to create a database cluster from the Myaccount portal The tutorial that is mentioned below are the basic steps of getting started with the Relational Database cluster in Myaccount Portal Login into MyAccount Portal Please Login to Myaccount Portal using your credentials set up at the time of creating and activating the E2E Networks My Account Navigate to Database Page Once you have logged in to Myaccount Portal You can navigate to the database page from the sidebar menu Create Database On the top right section of the manage database dashboard You need to click on the Create Database Button which will prompt you to the cluster page where you will be selecting the configuration and entering the details of your database Database Configuration and Setting Database Please choose a database of your preference from options such as MySQL MariaDB PostgreSQL MongoDB along with the specific version Each database provides a range of database engines and versions for selection Please select the appropriate version corresponding to the database engine Currently we are displaying the MySQL version in the image Below are the list of database engine which we currently support Mysql 56 Mysql 57 Mysql 80 Mariadb 104 Mariadb 106 Mariadb 1011 PostgreSQL 100 PostgreSQL 110 PostgreSQL 120 PostgreSQL 130 PostgreSQL 140 PostgreSQL 150 mongoDB 60 Cluster Configuration Node Cluster configuration comprises varying combinations of CPU memory storage and gives you the flexibility to choose the appropriate mix of resources for your database After that click on next icon Plan After selecting versionyou will be redirected to plan section Here you need to select plan according to your need By clicking Version you can see the selected version Details After selecting the plan You need to select the required configuration and setting for your database which are mentioned below Name You need to Provide the Cluster name which you want for your cluster This name will be visible on the Database page Database Setting We need to update the database name user and provide a secure password for our database You will be using these credentials to log in to the database server With strong password authentication your database controls and authenticates user accounts If a DB engine has strong password management features they can enhance security Once you have entered the required details click on create a database Your database might take a few minutes to Launch The database node will be in a setting up state until its ready to use and when the status will change to running VPC If you want to attach VPC with your DBaas you can select if you have VPC it will show in the list or you can create a new VPC by clicking on Create New VPC By clicking Plan you can see the selected plan Click on Next button Summary After clicking on Next button you will move to the Summary sectionIn that you will see the selected details and click on Submit button DBaaS Details After successfully created DBaas You can see the details of it on DBaaS Details tab Connecting to your database Cluster After E2Es database DBS provision your nodes you can use any standard SQL client application to connect to a database on the DB instance In this example you connect to a database on a Maria DB instance using the MySQL commandline tool To connect to your database node using MySQL command line Once your database has been provisioned and its running status You can get the database connectivity information on the dashboard Usernames Host Details Port SSL Mode Enter the following command at a command prompt on your local or client desktop to connect to a MySQL database mysql h host P 3306 u username p password After you enter the password for the user you should see output similar to the following Welcome to the MySQL monitor Commands end with or g Your MySQL connection id is 272 Server version 55510017MariaDBlog MariaDB Server Copyright c 2000 2015 Oracle andor its affiliates All rights reserved Oracle is a registered trademark of Oracle Corporation andor its affiliates Other names may be trademarks of their respective owners Type help or h for help Type c to clear the current input statement mysql To connect to your database node using MariaDB command line Once your database has been provisioned and its running status You can get the database connectivity information on the dashboard Usernames Host Details Port SSL Mode Enter the following command at a command prompt on your local or client desktop to connect to a MariaDB database mysql h host P 3306 u username p password To connect to your database node using PostgreSQL command line Once your database has been provisioned and its running status You can get the database connectivity information on the dashboard Usernames Host Details Port SSL Mode Enter the following command at a command prompt on your local or client desktop to connect to a PostgreSQL database psql h host p 5432 U username d database To connect to your database node using mongoDB command line Once your database has been provisioned and its running status You can get the database connectivity information on the dashboard Usernames Host Details Port SSL Mode Enter the following command at a command prompt on your local or client desktop to connect to a mongoDB database mongosh host host u username p authenticationDatabase databasename Whitelisted IP Allow Trusted Host IPs This setting control the access of Allowed Host IP that can be able to connect your Database node from your trusted ISP IP If No trusted host selected Anyone can connect using credentials Click on Add icon to add a new trusted IP address to the list Instead of using the default local loopback IP address 127001 provide the private IP address of the node you want to whitelist Confirm and save the changes The green mark likely indicates a successful addition of the trusted IP If you want to categorize or label the trusted IP for organizational purposes you can add a tag with a custom name Now you have successfully whitelisted the node IP in the DBaaS environment Additionally always follow best practices for securing databases and regularly monitor this helps to prevent brute force password and denialofservice attacks from any server not explicitly permitted to connect Snapshots The snapshot feature is valuable for data protection disaster recovery and testing scenarios providing users with the ability to easily revert to a previous database state or create duplicates for various purposesand we use restore snapshot to quickly recover lost or corrupted data recover from system failures and revert to a stable state in case of issues during testing or updates Its like a fastforward button to a previously known good state of a system Take Manual Snapshot of Database When the user wants to take a snapshot immediately and manually they can click on the take snapshot button After clicking on the take snapshot button A popup menu will appear prompting you to enter the snapshot name Provide the snapshot name and click on create snapshot to initiate the snapshot creation Restore Snapshot To restore the snapshot from the saved file click the action button select the restore option and proceed with the snapshot restoration Delete Snapshot When a user wants to deletes the snapshot they can remove from the snapshot list To delete a snapshot click the action button select the delete option and confirm the deletion of the snapshot Scheduled snapshot scheduled snapshot is a proactive approach to data management and system backup providing regular and automated snapshots to enhance data protection disaster recovery and overall system reliability When a user wants to schedules a time duration a snapshot will be created every day within the specified timeframe To schedule a snapshot of your database click on the Schedule link Choose the snapshot creation interval and select the desired time duration for taking snapshots Edit Scheduled Snapshot When a user wants to edit the scheduled snapshot interval they can modify the time duration for the scheduled snapshot changes To edit the scheduled snapshot of your database click on the Edit link Select the desired options and save the changes to the scheduled snapshot After editing the scheduled snapshot for your database you can disable the scheduled snapshot Schedule Lifecycle To configure the Schedule lifecycle of your database click on Schedule lifecycle and select the option to configure the snapshot lifecycle When a user selects the snapshot lifecycle the snapshot is automatically deleted after the specified time duration Note Snapshot will be deleted automatically after the selected interval Edit configure Snapshot lifecycle To edit the Configure scheduled snapshot of your database click on the Edit Configure Scheduled Snapshot button Select the desired options and save the changes to the scheduled snapshot When a user edits the snapshot lifecycle the time duration for the snapshot Lifecycle changes After editing the configure snapshot lifecycle for your database you can disable the configure snapshot lifecycle Read Replica The read replica operates as a DB instance that allows only readonly connections Applications can connect to a read replica just as they would to any DB instance Note The size of readonly nodes can not be set individually and are tied to the size of the DBaaS primary node Due to this readonly nodes must be at least as big as your DBaaSs primary node and will be automatically scaled to match Monitoring After you launch your database node you can view the monitoring graphs for your node on the Monitoring tab Each graph is based on one of the different metrics This information is collected from your node and processes raw data into readable graphs Monitoring is an important part of maintaining the reliability availability and performance of your database Alerts You can set up new alerts by defining trigger parameters as per your use case for your database The alerting system works by sending automatic response notifications to your defined email list After clicking click here link you will be redirected to Create Alert popup page In that you have to select Trigger Type and select Trigger Condition Enter Trigger value In that you have to select Trigger Duration and then click on Submit button After successfully creation of alert you can see the list below Slow Log Queries The slow query log feature in MySQL allows you to log all queries that take longer than a given threshold of execution time The queries in the slow query log are good candidates to start optimizing and eliminating the bottlenecks To configure slow log queries Click on configure view and select the appropriate time duration to log the queries that will be displayed on the dashboard Managing Your Database Node In this section you can find instructions and details to Manage and Maintain your database To manage your Database Instance Click on Action Button and Select Manage option for your database Node Stopping your Database If you are using your DB Node for temporary testing or for any other daily development activity and want to test out your database by stopping it which will close all the connections in your database You can perform this action by clicking on Action and selecting the Stop button Starting your Database You can resume your database which was stopped earlier by clicking on the Start button in the Action menu Resuming your database will retain the same IP and credentials for your database and there will not be any changes at configuration level Restart If you are testing out your DB nodes restarting your database to reset connections or for any troubleshooting purpose You can restart your database by clicking on the Restart button on the action menu Upgrade your database The DBaaS upgrade feature enables customers to easily upgrade their DBaaS plan based on their specific usage requirements For upgrading you database you have to click on Upgrade button under Action button Before upgrading you need to stop your DBaas first After clicking on Upgrade the Upgrade plan will be show and you have to click on Upgrade button with the selected plan after that the confirmation popup will be open and you have to click on Upgrade button After this the Upgrading process will be start and the database status will be in upgrading status Note Please ensure that your database is stopped when performing the upgrade action Delete your Database To delete your database click on Delete option Please note that once you have deleted your database you will not be able to recover your database After clicking on delete you will see the popup and click on delete On this page Introduction Benefits Easy Administration Scalability and Failover Speed Secure Getting Started with Database How to Create a Database Cluster in Myaccount Portal Login into MyAccount Portal Navigate to Database Page Create Database Database Configuration and Setting Database Plan Details Summary DBaaS Details Connecting to your database Cluster To connect to your database node using MySQL command line To connect to your database node using MariaDB command line To connect to your database node using PostgreSQL command line To connect to your database node using mongoDB command line Whitelisted IP Snapshots Take Manual Snapshot of Database Restore Snapshot Delete Snapshot Read Replica Monitoring Alerts Slow Log Queries Managing Your Database Node Stopping your Database Starting your Database Restart Upgrade your database Delete your Database Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited


cPanel Linux Cloud Claim your spot on the waitlist for the NVIDIA H100 GPUs Join WaitlistE2E CloudProductsPricingPartnersEventsCareersCompanyInvestorContact UsBlogLoginLoginSign UpcPanel WHM Integrated Cloud Servers with LicenseFull Root access cPanel WHM preinstalled VMs All plans include licensing at no extra cost Manage security with Bitninja Oneclick install 450 apps with SoftaculousLaunch GPUContact SalesCheck Out The Pricing By Clicking HereProduct Enquiry Form Name RequiredEmail RequiredPhone RequiredCompany OptionalThank you Your submission has been received An expert from our sales team will contact you shortlyOops Something went wrong while submitting the formTable of ContentsExample H2Example H3Example H4Example H5Example H6Multiple Usecases One SolutionE2Es GPU Cloud is suitable for a wide range of usesBenefits of E2E GPU CloudNo Hidden FeesNo hidden or additional charges What you see on pricing charts is what you payNVIDIA Certified Elite CSP PartnerWe are NVIDIA Certified Elite Cloud Service provider partner Build or launch preinstalled software Cloud GPUs to ease your workNVIDIA Certified HardwareWe are using NVIDIA certified hardware for GPU accelerated workloadsFlexible PricingWe are offering pay as you go model to long tenure plans Easy upgrade allowed Option to increase storage allowedGPUaccelerated 1click NGC ContainersE2E Cloud GPUs have super simple one click support for NGC containers for deploying NVIDIA certified solutions for AIMLNLPComputer Vision and Data Science workloadsTrusted by 15000 ClientsView More Documentation ResourcesHow To Install Woocommerce In cPanelKnow the best ways to install WooCommerce The best WordPress plugin that can be used to create a website very quicklyRead MoreWHM To WHM Migration With Root AccessIf you have root access for both the source server and destination server then follow the below stepsRead MoreInstalling Magento On CpanelLearn how you can install Magento on cPanel with simple stepsRead MoreI recently signed up with E2E Networks for their Cloud Server services and I have been very impressed with their Linux servers The service is not only very affordable but it also offers great performance and reliability I would highly recommend E2E Networks to anyone looking for a reliable and costeffective cloud server provider especially for Indian clients Proud WadhwaDjango Developer Great Future Technology Pvt LtdThis is one of the best cloud server providers as we are part of this provider and using it the service and other things are good and accurateHardeep Singh AhluwaliaSenior Manager IT Infra Successive TechnologiesWe have been using E2E Networks for the past 6 months and I am extremely satisfied with the service and the customer support Their servers are quite reliable and very costeffective especially the GPU machines The team is always ready to solve any problem however small Very happy to make E2E Networks our longterm partnersHarshit AgrawalData Scientist at Studio SirahHave been using E2E Networks infra for a decade now and never had any issues Scootsy ran 80 of the workload on E2E Networks before it was acquired by SwiggyKunal ShethFounder GottaGo Ex CTO at ScootsyAntfarm We at CamCom are using E2E GPU servers for a while now and the priceperformance is the best in the Indian market We also have enjoyed a fast turnaround from the support and sales team always I highly recommend the E2E GPU servers for machine learning deep learning and Image processing purposeMr Uma MaheshCOO at CamCom AIE2E Cloud is NextGen PaaS IaaS provider It is a fully augmented and automated platform that is the best in practice in the current Cloud market We are using E2E Networks for more than 5 years and are very much satisfied with the deliverables They have very affordable pricing and are changemaker in the Indian Hosting IndustryMr Devarsh PandyaFounder at CantechE2E GPU machines are superior in terms of performance and at the same time you end up saving more money compared to AWS and Azure Not to mention the agility and skilled customer support that comes alongArvind SainiVP of Engineering at Crownit GoldVIPThe customer support that E2E has provided us is beyond exceptional Their quick response is what makes them stand apart from others and is second to none in the cloud space Weve been using their GPU instances for our Deep Learning workloads for quite a long time The quality of service is amazing at a competitive price and we strongly recommend E2EAkshay Kumar CFounder COO at Marsviewai incCongratulations Thanks for the fast reliable and costeffective solution for my small startup since Mar 2016Ratul NandiLead Software Engineer Gartner previously CEBYou guys are doing everything perfectly I couldnt ask for anything more Keep it up Very happy with the serviceMr Mayank MalhotraDirector ZenwebnetE2E Networks has helped me reach my 1st goal with its cloud platform They gave us a trial to get used to the service Happy with their product will surely recommend others to try it once Good support so farShahnawaz Alam CTO HW Wellness Solutions Pvt LtdFor most startups AWS EC2 is unnecessarily costly Even better for India get a machine from E2E NetworksNaman SarawagiFounder FindYogiI am very much happy with E2E Networks Pvt Ltd Im using your services for the past year and I have provided E2E with multiple clients Whoever is looking for servers I strongly recommend E2E NetworksProtik BanerjeeRelcode Technology Pvt LtdI had a pleasant experience with E2E Network when I purchase the cPanel license plan They provided the onboarding support when I generated a ticket for the purchase Everything was delivered swiftly without any problemsChaitanyakumar GajjarFounder Infinity Software SolutionsPlease reach out to e2e networks if you need any cloud services their service is awesome I want to rate 55 for their servicesShreekethIssaniWe are using E2E Cloud servers since last 2 years Very happy with costeffective and highperformance compute nodes We were able to reduce our hosting expenses by 40 without compromising on quality security and stabilityVinod PandeyCofounder CTO myCBSEguideReally good service from E2E Networks And at very affordable prices We are satisfied with them The Cloud console access feature is a very good and very easy user interface And I am satisfied with the service features and Highperformance network for data uploaddownloadVarun SharmaCeo WebFreakSolutionEasy to Manage Easy to pay Low Cost Charan SinghSr Manager Crayons Advertising Pvt LtdI have been using E2E Cloud for almost a year now These guys are the most professional of all the cloud providers in India They have absolutely reliable products and also charge the lowest rate I would like to recommend it to all who are looking for COST Effective cloud serversNaresh KumarSystem Administrator Aravali College of Engg MgmtOur experience with E2E has been better than AWS as our website is performing better both in terms of latency and uptime Since E2E provides plans that are simple to understand implement and are a complete package our efforts are concentrated on the development and not on maintaining the infrastructureArjun GuptaSenior Manager Pharma Synth Formulations LimitedWe have been using Kubernetes cluster on E2E Cloud and are reasonably satisfied with its performance We were able to reduce our costs by 40 after migrating from Azure My big thanks to the E2E Cloud team for launching a Cloud and helping Indian startups in reducing their cloud costsAmarjeet SinghCoFounder CTO ZenatixThe platform is comfortable support is good 2 years anniversary completed in E2EMr Yonti LevinCoFounder CTO at LooraAbout UsE2E Networks Ltd is an Indiafocused Cloud Computing Company pioneering the introduction of contractless cloud computing for Indian startups and SMEs The E2E Networks Cloud has been employed by numerous successfully scaledup startups such as Zomato Cardekho Healthkart Junglee Games 1mg and many others It played a crucial role in facilitating their growth from the startup stage to achieving multimillion Daily Active Users DAUsLearn MoreWhat Our Customers SayFor over a decade we have delighted our customers with stellar infrastructure and supportI recently signed up with E2E Networks for their Cloud Server services and I have been very impressed with their Linux servers The service is not only very affordable but it also offers great performance and reliability I would highly recommend E2E Networks to anyone looking for a reliable and costeffective cloud server provider especially for Indian clients Proud WadhwaDjango Developer Great Future Technology Pvt LtdPress and Media MentionsListed on NSE Emerge Backed by Blume Ventures Loved by PressFrequently Asked QuestionsWhat is a cPanel Cloud Server It is a virtual linux machines or a virtual private server that comes with preinstalled cPanel WHMIs the cPanel license cost included Yes all the plans are including the cPanel licensing cost You dont have to buy a separate license Well provide one by default Build on the most powerful infrastructure cloudGet Started for FreeContact SalesProductsCPU Intensive CloudHigh Memory CloudLinux Smart DedicatedcPanel Linux CloudWindows CloudWindows SQL CloudPlesk Windows CloudGPU Smart DedicatedLoad BalancerCompanyAbout UsMeet the TeamBecome a PartnerE2E in MediaTestimonialsInvestorsCareersContact UsContact SalesEscalation MatrixService Level AgreementTerms of ServicePrivacy PolicyRefund PolicyPolicy FAQResourcesBlogEventsService Health StatusHelpWhitePapersEcosystem EnablersCustomersCertificationsCountries ServedFAQsE2E CloudE2E Networks Limited is Indias fastest growing accelerated cloud computing playerSubscribe to our newsletterGet latest news articles resources and trends delivered to your inbox weeklyThank you Your submission has been receivedOops Something went wrong while submitting the formCIN Number L72900DL2009PLC341980 Copyright 2024 E2E Networks Limited YouTubeInstagram


Frequently Asked Questions FAQs E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction How to Create EQS Actions Add Queue under tab Actions for queue service Using SDK Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS How to Create Functions Functions Information Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group How to create Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registry Simplifying Pull Operations with UserFriendly Interface API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation E2E Networks Kubernetes Service Frequently Asked Questions FAQs Frequently Asked Questions FAQs What is a node pool A node pool is a group of nodes within a cluster that all have the same configuration or Node pools are independent groups of worker nodes belonging to a cluster where all nodes within a pool share a common configuration What is the minimum limit of nodes in Node pool Minimum 2 nodes are required in a combination of node pools What is the Maximum limit of node pools Max number of node pools is 20 Do I get access to the node in my node pool You cant access your worker node by using an SSH connection On this page What is a node pool What is the minimum limit of nodes in Node pool What is the Maximum limit of node pools Do I get access to the node in my node pool Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited


3 NGINX Ingress Controller E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction How to Create EQS Actions Add Queue under tab Actions for queue service Using SDK Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS How to Create Functions Functions Information Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group How to create Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registry Simplifying Pull Operations with UserFriendly Interface API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation E2E Networks Kubernetes Service 3 NGINX Ingress Controller 3 NGINX Ingress Controller The NGINX Ingress Controller is a popular opensource project that extends Kubernetes to manage and load balance application traffic within a cluster It acts as an Ingress resource for Kubernetes providing advanced features and capabilities for routing and managing HTTP HTTPS and TCP traffic to services in the cluster Here are some key features and functions of the NGINX Ingress Controller Ingress Resource Management It extends Kubernetes Ingress resource by adding more features and flexibility for routing traffic to services based on hostnames paths and other criteria Load Balancing The controller can distribute incoming traffic to different backend services based on rules defined in the Ingress resource It supports roundrobin least connections and IP hash load balancing methods SSLTLS Termination It can terminate SSLTLS encryption for incoming traffic enabling secure communication between clients and services Rewrites and Redirections The controller allows you to define URL rewrites and redirections to customize the behavior of incoming requests PathBased Routing You can route traffic based on the URL path to different services allowing for microservices architecture and application segregation Web Application Firewall WAF It supports the integration of Web Application Firewall WAF solutions for enhanced security Custom Error Pages You can define custom error pages for specific HTTP error codes TCP and UDP Load Balancing Besides HTTPHTTPS traffic the controller can handle TCP and UDP traffic as well Authentication and Authorization It can be configured to enforce authentication and authorization for incoming requests Custom Configurations You can customize NGINX configurations to meet specific requirements by using ConfigMaps and Annotations AutoScaling The controller can automatically scale the number of NGINX pods to handle increased traffic load Metrics and Monitoring It provides metrics and logs for monitoring and troubleshooting When NGINX is deployed to your DigitalOcean Kubernetes DOKS cluster a Load Balancer is created as well through which it receives the outside traffic Then you will have a domain set up with A type records hosts which in turn point to your load balancers external IP So data flow goes like this User Request HostDOMAIN Load Balancer Ingress Controller NGINX Backend Applications Services In a real world scenario you do not want to use one Load Balancer per service so you need a proxy inside the cluster which is provided by the Ingress Controller As with every Ingress Controller NGINX allows you to define ingress objects Each ingress object contains a set of rules that define how to route external traffic HTTP requests to your backend services For example you can have multiple hosts defined under a single domain and then let NGINX take care of routing traffic to the correct host The NGINX Ingress Controller is deployed via Helm and can be managed the usual way To know more about the community maintained version of the NGINX Ingress Controller check the official Kubernetes documentation Getting Started After Deploying NGINX Ingress Controller Please refer to this document to connect your kubernetes cluster httpsdocse2enetworkscomkuberneteskuberneteshtmlhowtodownloadkubeconfigyamlfile Once you have set up your cluster using kubectl proceed with executing the following commands helm repo add ingressnginx httpskubernetesgithubioingressnginx helm repo update Confirming that NGINX Ingress Controller is running First check if the Helm installation was successful by running command below helm ls n ingressnginx The Status column value should be deployed Next verify if the NGINX Ingress Controller Pods are up and running kubectl get pods allnamespaces l appkubernetesionameingressnginx Pods Should be in Ready State and Running Status Finally inspect the external IP address of your NGINX Ingress Controller Load Balancer by running below command kubectl get svc n ingressnginx Check if Valid IP is attached to the Service of Type LoadBalancer If externalip of service of type LoadBalancer is in pending status and you dont have any available ip Then attach ip to the cluster from LB IP POOL Tab To attach Ip to the cluster please refer this link httpsdocse2enetworkscomkuberneteskuberneteshtmlloadbalancer To see how to get domain name attach to ip lease please refer this link httpsdocse2enetworkscomnetworkingdnshtml Tweaking Helm Values The NGINX Ingress stack provides some custom values to start with See the values file from the main GitHub repository for more information You can inspect all the available options as well as the default values for the NGINX Ingress Helm chart by running the following command helm show values ingressnginxingressnginx version 472 After customizing the Helm values file valuesyml you can apply the changes via helm upgrade command as shown below helm upgrade ingressnginx ingressnginxingressnginx version 472 namespace ingressnginx values valuesyml Configuring NGINX Ingress Rules for Services To expose backend applications services to the outside world you specify the mapping between the hosts and services in your Ingress Controller NGINX follows a simple pattern in which you define a set of rules Each rule associates a host to a backend service via a corresponding path prefix Typical ingress resource for NGINX looks like below apiVersion networkingk8siov1 kind Ingress metadata name servicea name of your choice spec ingressClassName nginx rules host ingressmyexamplecom http paths path pathType Prefix backend service name servicea name of service you want to run port number 80 value of port on your service Explanations for the above configuration specrules A list of host rules used to configure the Ingress If unspecified or no rule matches all traffic is sent to the default backend specruleshost Host is the fully qualified domain name of a network host eg ingressmyexamplecom specruleshttp List of http selectors pointing to backends specruleshttppaths A collection of paths that map requests to backends In the above example the path prefix is matched with the echo backend service running on port 80 The above ingress resource tells NGINX to route each HTTP request that is using the prefix for the ingressmyexamplecom host to the echo backend service running on port 80 In other words every time you make a call to httpingressmyexamplecom the request and reply will be served by the echo backend service running on port 80 If you want to make a request on httpsingressmyexamplecom then you must need a tlsssl certificate Typical NGINX Ingress Rule for such case is apiVersion networkingk8siov1 kind Ingress metadata name servicea name of your choice spec ingressClassName nginx rules host ingressmyexamplecom http paths path pathType Prefix backend service name servicea name of service you want to run port number 80 tls hosts ingressmyexamplecom secretName serviceasecret Explanations for the above configuration spectls A collection of list of hosts and secretName NOTE SecretName is the same secret you have created while creating certificate using certmanager Please refer to the certmanager documentation for further information httpsdocse2enetworkscomkuberneteskubernetesmarketplacehtmlcertmanager For further information you can follow ingress documentation Upgrading the NGINX Ingress Chart You can check what versions are available to upgrade by navigating to the ingressnginx official releases page on GitHub Alternatively you can also use ArtifactHUB Then to upgrade the stack to a newer version run the following command helm upgrade ingressnginx ingressnginxingressnginx version INGRESSNGINXSTACKNEWVERSION namespace ingressnginx values YOURHELMVALUESFILE See helm upgrade for more information about the command Upgrading With Zero Downtime in Production By default the ingressnginx controller has service interruptions whenever its pods are restarted or redeployed In order to fix that see this blog post by Lindsay Landry from Codecademy Uninstalling the NGINX Ingress Controller To delete your installation of NGINX Ingress Controller run the following command helm uninstall ingressnginx n ingressnginx NOTE The command will delete all the associated Kubernetes resources installed by the ingressnginx Helm chart except the namespace itself To delete the ingressnginx namespace as well please run below command kubectl delete ns ingressnginx On this page Getting Started After Deploying NGINX Ingress Controller Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited


E2E Networks Documentation E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs 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mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registery API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks Documentation Welcome to E2E Networks platform documentation E2E Networks Limited is Indias leading NSElisted AIfirst hyperscale cloud provider Here users will find detailed guides tutorials and troubleshooting tips covering a wide range of topics from CPU and GPU compute usage to TIR AI Platform Kubernetes services Terraform our ecosystem of cloud technologies our APIs and SDK storage solutions and about our DBaaS platform You will also find help on our Billing and Payment system security and our processes for handling abuse You will also find tutorials that help you get started with building applications in the AIML domain Finally you can also check out our release notes for latest features fixes and updates released on Myaccount Getting Started To get started head to Myaccount and follow the sign up process explained here Note that the process is slightly different for Indian individiuals Indian organizations and International organizations Click here to get started Our AIFirst Infrastructure E2E Networks advanced cloud GPUs offer developers unprecedented access to highperformance computing resources essential for tackling intensive tasks like machine learning deep learning and complex data analytics Our GPUs ranging from HGX 8xH100 A100 clusters L4OS T4 and others are integrated into E2Es cloud infrastructure and provide a highend platform to developers for AI inference and development Get started with our GPU nodes here TIR AI Platform TIR is a modern AI Development Platform designed to tackle the friction of training and serving large AI models TIR uses highly optimised GPU containers NGC preconfigured environments pytorch tensorflow triton automated API generation for model serving shared notebook storage and much more Learn more about TIR here On this page Getting Started Our AIFirst Infrastructure TIR AI Platform Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited


Step by Step Guide to FineTuning BLOOM E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registery API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation Welcome to TIR AI Platform Documentation Tutorials Step by Step Guide to FineTuning BLOOM Step by Step Guide to FineTuning BLOOM Introduction BLOOM is a powerful tool that can be used for a variety of tasks including Text generation BLOOM can generate text in any of the languages it was trained on including creative text formats such as poems code scripts musical pieces email and letters Translation BLOOM can translate text from one language to another with high accuracy Code generation BLOOM can generate code in a variety of programming languages including Python Java C and JavaScript Question answering BLOOM can answer your questions in a comprehensive and informative way even if they are open ended challenging or strange BLOOM is still under development but it has the potential to revolutionize the way we interact with computers It can be used to create new and innovative applications in a wide range of fields including education healthcare and business One of the key benefits of BLOOM is that it is opensource and openaccess This means that anyone can use BLOOM to develop new applications or to explore the capabilities of LLMs This is a significant step forward in the field of AI as it democratizes access to LLM technology and makes it possible for more people to benefit from its capabilities What Is FineTuning Finetuning is a technique in machine learning where a pretrained model is adapted to a new task by training it on a small amount of data that is specific to the new task This is different to training a model from scratch which requires a large amount of data and can be timeconsuming Finetuning is a powerful technique for training LLMs on new tasks BLOOM is a pretrained LLM so it can be finetuned to perform a variety of tasks such as generating text translating languages and writing creative content Why FineTune BLOOM There are several reasons why you might want to finetune BLOOM To improve the performance of BLOOM on a specific task For example you could finetune BLOOM to generate more creative texts or to translate languages more accurately To adapt BLOOM to a new domain For example you could finetune BLOOM to generate text in a specific industry or to translate languages from a specific region To develop a custom LLM that is tailored to your specific needs For example you could finetune BLOOM to generate text that is specific to your company or to translate languages that are relevant to your research Benefits of FineTuning BLOOM Finetuning BLOOM offers a number of benefits including Improved performance on specific tasks Adaptation to new domains Development of custom LLMs Reduced training time and cost Finetuning BLOOM can be a relatively quick and easy way to improve the performance of BLOOM on a specific task or to adapt BLOOM to a new domain This can be a significant advantage over training a model from scratch which can be timeconsuming and expensive Requirements Python Libraries To finetune BLOOM a user needs the following A notebook backed by a GPU Finetuning BLOOM requires a GPU with at least 4GB of memory However this can handle only basic operations and higher functions require higher memory Python programming language Transformers library BLOOM model and tokenizer A training dataset The training dataset should be a collection of text examples that are relevant to the task The following steps can be followed to finetune BLOOM Install the required Python libraries Download the BLOOM model and tokenizer Load your training data Prepare your training data Define your training arguments Train the model Evaluate the model Save the finetuned model In addition to the requirements listed above there are a few other things to keep in mind while finetuning BLOOM The size of the training dataset The larger the training dataset the better the finetuned model will perform The quality of your training dataset The training dataset should be highquality and representative of the task that you want to finetune BLOOM for The hyperparameters that you use for training The hyperparameters control the training process such as the number of training epochs and the learning rate It is important to tune the hyperparameters to get the best performance from the finetuned model Launch Your GPUBacked Notebook Head over to E2E Cloudhttpsmyaccounte2enetworkscom and sign in or register Once through click on the top left corner to head to TIR AI Platform Then click on Create a Notebook Create Notebook on TIR Make sure you select GPU notebook Free credits are available which should easily suffice for this tutorial Once notebook has been launched follow through the next steps Packages and Libraries You will have to install the following libraries pip install transformers pip install accelerate U pip install datasets import transformers from transformers import BloomForCausalLM from transformers import BloomForTokenClassification from transformers import BloomTokenizerFast from transformers import TrainingArguments from transformers import Trainer from transformers import AutoTokenizer from transformers import DataCollatorWithPadding import torch from datasets import loaddataset import random BLOOM Model and Tokenizer To finetune BLOOM the user will need to load their training data The training data should be a collection of text examples that are relevant to the task that the user wants to finetune BLOOM for For example if the user wants to finetune BLOOM to generate more creative texts they could use a training dataset of poems code scripts musical pieces email and letters If the user wants to finetune BLOOM to translate languages more accurately they could use a training dataset of parallel text in multiple languages Once the user has collected their training data they need to convert it to a format that can be used by the BLOOM model The BLOOM model expects the training data to be in a tokenized format To tokenize the training data the user can use the BLOOM tokenizer The BLOOM tokenizer will split the training data into individual tokens which are the basic units of text that the BLOOM model can understand Here is an example of how to tokenize the training data using the BLOOM tokenizer import transformers tokenizer BloomTokenizerFastfrompretrainedbigsciencebloom1b7 Load the training data trainingdata with opentrainingdatatxt r as f for line in f trainingdataappendlinestrip Tokenize the training data tokenizedtrainingdata tokenizertrainingdata returntensorspt Training Data To prepare the training data for training the user needs to split the tokenized training data into pairs of input and target sequences The input sequence is the text that the BLOOM model should predict and the target sequence is the text that the BLOOM model should predict For example if the user is finetuning BLOOM to generate text their training dataset might look like this Input sequence I am a cat Target sequence Meow Input sequence I love to play Target sequence Fun Once the user has created a training dataset they need to split it into training and validation sets The training set should be about 80 of the total dataset and the validation set should be about 20 of the total dataset To split the dataset the user can use the following Python code import random Split the dataset into training and validation sets traindataset valdataset for inputids attentionmask in tokenizedtrainingdata if randomrandom 08 traindatasetappendinputids attentionmask else valdatasetappendinputids attentionmask Example Suppose tokenizedtrainingdata is a list containing the following pairs of inputids and attentionmask tokenizedtrainingdata 1 2 3 1 1 1 4 5 6 1 1 1 7 8 9 1 1 1 10 11 12 1 1 1 After running the above code the user might end up with traindataset and valdataset similar to the following traindataset 1 2 3 1 1 1 7 8 9 1 1 1 valdataset 4 5 6 1 1 1 10 11 12 1 1 1 Training the BLOOM Model To train the BLOOM model the user can use the Trainer class from the Transformers library The Trainer class provides a number of features that make it easy to train and evaluate LLMs such as Automatic gradient computation Distributed training Early stopping Evaluation metrics To train the BLOOM model using the Trainer class the user can use the following Python code pip install transformers pip install accelerate U pip install datasets import transformers from transformers import BloomForCausalLM from transformers import BloomForTokenClassification from transformers import BloomTokenizerFast from transformers import TrainingArguments from transformers import Trainer from transformers import AutoTokenizer from transformers import DataCollatorWithPadding import torch from datasets import loaddataset Load the BLOOM model and tokenizer model BloomForCausalLMfrompretrainedbigsciencebloom1b7 tokenizer BloomTokenizerFastfrompretrainedbigsciencebloom1b7 Create the training dataset rawdatasets loaddatasetglue mrpc checkpoint bertbaseuncased tokenizer AutoTokenizerfrompretrainedcheckpoint def tokenizefunctionexample return tokenizerexamplesentence1 examplesentence2 truncationTrue tokenizeddatasets rawdatasetsmaptokenizefunction batchedTrue datacollator DataCollatorWithPaddingtokenizertokenizer traindatasettokenizeddatasetstrain Create the validation dataset evaldatasettokenizeddatasetsvalidation Define the training arguments trainingargs TrainingArguments outputdiroutput numtrainepochs10 perdevicetrainbatchsize16 perdeviceevalbatchsize8 learningrate2e5 Create the trainer trainer Trainer model trainingargs traindatasettraindataset evaldatasetevaldataset datacollatordatacollator tokenizertokenizer Train the model trainertrain Evaluation To evaluate the finetuned BLOOM model the user can use the following Python code Evaluate the model on the test dataset testaccuracy trainerevaluatetestdataset The test loss and accuracy will give the user an indication of how well the finetuned BLOOM model will perform on new data If the test loss and accuracy are satisfactory the user can use the finetuned model to generate text translate languages and write creative content Here are some tips for finetuning BLOOM Use a large and representative training dataset The larger and more representative the training dataset is the better the finetuned model will perform Use a suitable learning rate The learning rate controls how quickly the model learns A toohigh learning rate can cause the model to overfit the training data while a toolow learning rate can cause the model to learn slowly Use early stopping Early stopping prevents the model from overfitting the training data by stopping training when the validation loss stops decreasing Experiment with different hyperparameters The hyperparameters of the training process can have a significant impact on the performance of the finetuned model Experiment with different hyperparameters to find the best combination for the users task Saving and Loading Once the user has trained and evaluated the finetuned BLOOM model they can save it to a file so that they can use it later To do this the user can use the savepretrained method of the Trainer class Load the finetuned BLOOM model model BloomForCausalLMfrompretraineddirectory Save the finetuned model to a file modelsavepretraineddirectory Once the user has saved the finetuned model they can load it back into memory using the frompretrained method Load the finetuned BLOOM model model BloomForCausalLMfrompretraineddirectory The user can then use the finetuned model to generate text translate languages and write creative content Example Let us test BLOOM with various prompts The required packages are first installed and necessary libraries are imported pip install transformers from transformers import BloomForCausalLM from transformers import BloomForTokenClassification from transformers import BloomTokenizerFast import torch The BLOOM model is then imported to the local drive Here 1b7 version of bloom is imported into the system The size of the model is 344 GB tokenizer BloomTokenizerFastfrompretrainedbigsciencebloom1b7 localfilesonlyFalse model BloomForCausalLMfrompretrainedbigsciencebloom1b7 localfilesonlyFalse Once the pretrained model is downloaded we can then move to giving different prompts as inputs prompt resultlength inputs tokenizerprompt returntensorspt printtokenizerdecodemodelgenerateinputsinputids maxlengthresultlength numbeams2 norepeatngramsize2 earlystoppingTrue 0 Example 1 Let us consider generating text related to E2E Cloud BLOOM has no prior awareness of it But it has to generate text based on its training even without knowing about E2E The required length is 50 characters prompt E2E cloud is a cloud service provider It is resultlength 50 inputs tokenizerprompt returntensorspt Output E2E cloud is a cloud service provider It is the only cloud provider in the world that provides a complete cloud solution for the entire enterprise The company is based in Singapore and has offices in Hong Kong Singapore and the United States From the output it can be seen that the model has given wrong information but it is somewhat believable to someone who does not know about the company The generated text attributes characteristics and locations to the company based on what the model has learned during its training although these details might not be accurate because the model is not aware of the specific company This highlights both the flexibility and the limitations of such largescale language models Example 2 Let us consider generating text related to some generic content in this case an animal The prompt given is Jaguars are wild species they with the required length of 50 characters prompt Jaguars are wild species they resultlength 50 inputs tokenizerprompt returntensorspt Output Jaguars are a wild species they are not easy to domesticate and they have a tendency to become aggressive They are also very territorial so it is important to keep them in a small space BLOOM demonstrates its ability to produce factual and contextually relevant information about jaguars a wild animal species This suggests that BLOOM is wellequipped to handle generalized queries synthesizing its vast training data into an accurate and informative output Overall this example showcases the models strength in producing reliable and coherent text when presented with a generic topic Example 3 Let us consider generating a longer text with a question The text asked is a technical question The prompt given is What is deep learning with a required length of 200 characters prompt What is deep learning resultlength 200 inputs tokenizerprompt returntensorspt Output What is deep learning Deep learning is a machine learning technique that uses a large amount of data to learn a model that can be used to solve a specific problem Deep neural networks DNNs are a type of machinelearning algorithm that learns from data They are used in a wide range of applications including computer vision speech recognition and natural language processing The DNN is trained using a set of labeled data which is called the training set Once trained the model is able to generalize well to unseen data Deep learning has been used for a variety of tasks such as image classification text categorization image captioning object detection etc In this paper we focus on the task of image segmentation Image segmentation is the process of identifying and classifying the objects in an image There are two main types of segmentation algorithms regionbased and objectbased Regionbased algorithms segment the image into regions based on certain criteria while object BLOOM takes on a technical question about deep learning and provides a comprehensive answer within the 200character limit BLOOM effectively demonstrates its capability to not only answer a question but also provide contextual background information thereby giving the reader a rounded understanding of the subject This example exemplifies BLOOMs prowess in generating detailed informative and relevant content in response to technical queries Conclusion Here are some example use cases for finetuned BLOOM Generating creative text Finetuned BLOOM can be used to generate creative text such as poems code scripts musical pieces email and letters Translating languages Finetuned BLOOM can be used to translate languages more accurately and fluently Answering questions Finetuned BLOOM can be used to answer questions in a more comprehensive and informative way Summarizing text Finetuned BLOOM can be used to summarize text more concisely and accurately These are just a few examples of the many possible use cases for finetuned BLOOM By finetuning BLOOM to a specific task you can unlock its full potential to generate creative text translate languages answer questions summarize text and write different kinds of creative contentFinetuning BLOOM is a powerful way to adapt the model to a specific task By following the tips in this guide users can finetune BLOOM to achieve good performance on a variety of tasks such as generating creative text translating languages answering questions summarizing text and writing different kinds of creative content Running BLOOM on a large scale requires a large RAM size and cloud E2E Cloud offers various cloud based GPU processors at a nominal cost If you require running BLOOM LLM consider using E2E cloud serviceshttpswwwe2enetworkscomproducts NVIDIA L4 and A100 GPUs are considered to be good for Natural Language processing Compare themhttpswwwe2enetworkscomblognvidial4vsa100gpuschoosingtherightoptionforyouraineeds to find which is more suitable to your requirements On this page Introduction What Is FineTuning Why FineTune BLOOM Benefits of FineTuning BLOOM Requirements Python Libraries Launch Your GPUBacked Notebook Packages and Libraries BLOOM Model and Tokenizer Training Data Example Training the BLOOM Model Load the BLOOM model and tokenizer Create the validation dataset Define the training arguments Create the trainer Evaluation Saving and Loading Example 1 Example 2 Example 3 Conclusion Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited


Nvidia V100 Tensor Core Cloud GPU 32 GB E2E Cloud Claim your spot on the waitlist for the NVIDIA H100 GPUs Join WaitlistE2E CloudProductsPricingPartnersEventsCareersCompanyInvestorContact UsBlogLoginLoginSign UpNVIDIA TESLA V100NVIDIA Tesla V100 Tensor Core is the most advanced data center GPU ever built to accelerate AI high performance computing HPC data science and graphicsLaunch GPUContact SalesCheck Out The Pricing By Clicking HereProduct Enquiry Form Name RequiredEmail RequiredPhone RequiredCompany OptionalThank you Your submission has been received An expert from our sales team will contact you shortlyOops Something went wrong while submitting the formTable of ContentsExample H2Example H3Example H4Example H5Example H6Multiple Usecases One SolutionE2Es GPU Cloud is suitable for a wide range of usesAIMLDLTrain complex models at high speed to improve predictions and decisions of your algorithms Use any framework or library TensorFlow PyTorch Caffe MXNet AutoKeras and many moreComputer VisionAccelerate Convolutional Neural Networks based on deeplearning workloads like video analysis facial recognition medical imaging and othersNatural Language ProcessingConversational AI technologies are becoming ubiquitous with countless products taking advantage of automatic speech recognition natural language understanding and speech synthesis coming to marketBenefits of E2E GPU CloudNo Hidden FeesNo hidden or additional charges What you see on pricing charts is what you payNVIDIA Certified Elite CSP PartnerWe are NVIDIA Certified Elite Cloud Service provider partner Build or launch preinstalled software Cloud GPUs to ease your workNVIDIA Certified HardwareWe are using NVIDIA certified hardware for GPU accelerated workloadsFlexible PricingWe are offering pay as you go model to long tenure plans Easy upgrade allowed Option to increase storage allowedGPUaccelerated 1click NGC ContainersE2E Cloud GPUs have super simple one click support for NGC containers for deploying NVIDIA certified solutions for AIMLNLPComputer Vision and Data Science workloadsTrusted by 15000 ClientsView More Documentation ResourcesRead MoreRead MoreRead MoreI recently signed up with E2E Networks for their Cloud Server services and I have been very impressed with their Linux servers The service is not only very affordable but it also offers great performance and reliability I would highly recommend E2E Networks to anyone looking for a reliable and costeffective cloud server provider especially for Indian clients Proud WadhwaDjango Developer Great Future Technology Pvt LtdThis is one of the best cloud server providers as we are part of this provider and using it the service and other things are good and accurateHardeep Singh AhluwaliaSenior Manager IT Infra Successive TechnologiesWe have been using E2E Networks for the past 6 months and I am extremely satisfied with the service and the customer support Their servers are quite reliable and very costeffective especially the GPU machines The team is always ready to solve any problem however small Very happy to make E2E Networks our longterm partnersHarshit AgrawalData Scientist at Studio SirahHave been using E2E Networks infra for a decade now and never had any issues Scootsy ran 80 of the workload on E2E Networks before it was acquired by SwiggyKunal ShethFounder GottaGo Ex CTO at ScootsyAntfarm We at CamCom are using E2E GPU servers for a while now and the priceperformance is the best in the Indian market We also have enjoyed a fast turnaround from the support and sales team always I highly recommend the E2E GPU servers for machine learning deep learning and Image processing purposeMr Uma MaheshCOO at CamCom AIE2E Cloud is NextGen PaaS IaaS provider It is a fully augmented and automated platform that is the best in practice in the current Cloud market We are using E2E Networks for more than 5 years and are very much satisfied with the deliverables They have very affordable pricing and are changemaker in the Indian Hosting IndustryMr Devarsh PandyaFounder at CantechE2E GPU machines are superior in terms of performance and at the same time you end up saving more money compared to AWS and Azure Not to mention the agility and skilled customer support that comes alongArvind SainiVP of Engineering at Crownit GoldVIPThe customer support that E2E has provided us is beyond exceptional Their quick response is what makes them stand apart from others and is second to none in the cloud space Weve been using their GPU instances for our Deep Learning workloads for quite a long time The quality of service is amazing at a competitive price and we strongly recommend E2EAkshay Kumar CFounder COO at Marsviewai incCongratulations Thanks for the fast reliable and costeffective solution for my small startup since Mar 2016Ratul NandiLead Software Engineer Gartner previously CEBYou guys are doing everything perfectly I couldnt ask for anything more Keep it up Very happy with the serviceMr Mayank MalhotraDirector ZenwebnetE2E Networks has helped me reach my 1st goal with its cloud platform They gave us a trial to get used to the service Happy with their product will surely recommend others to try it once Good support so farShahnawaz Alam CTO HW Wellness Solutions Pvt LtdFor most startups AWS EC2 is unnecessarily costly Even better for India get a machine from E2E NetworksNaman SarawagiFounder FindYogiI am very much happy with E2E Networks Pvt Ltd Im using your services for the past year and I have provided E2E with multiple clients Whoever is looking for servers I strongly recommend E2E NetworksProtik BanerjeeRelcode Technology Pvt LtdI had a pleasant experience with E2E Network when I purchase the cPanel license plan They provided the onboarding support when I generated a ticket for the purchase Everything was delivered swiftly without any problemsChaitanyakumar GajjarFounder Infinity Software SolutionsPlease reach out to e2e networks if you need any cloud services their service is awesome I want to rate 55 for their servicesShreekethIssaniWe are using E2E Cloud servers since last 2 years Very happy with costeffective and highperformance compute nodes We were able to reduce our hosting expenses by 40 without compromising on quality security and stabilityVinod PandeyCofounder CTO myCBSEguideReally good service from E2E Networks And at very affordable prices We are satisfied with them The Cloud console access feature is a very good and very easy user interface And I am satisfied with the service features and Highperformance network for data uploaddownloadVarun SharmaCeo WebFreakSolutionEasy to Manage Easy to pay Low Cost Charan SinghSr Manager Crayons Advertising Pvt LtdI have been using E2E Cloud for almost a year now These guys are the most professional of all the cloud providers in India They have absolutely reliable products and also charge the lowest rate I would like to recommend it to all who are looking for COST Effective cloud serversNaresh KumarSystem Administrator Aravali College of Engg MgmtOur experience with E2E has been better than AWS as our website is performing better both in terms of latency and uptime Since E2E provides plans that are simple to understand implement and are a complete package our efforts are concentrated on the development and not on maintaining the infrastructureArjun GuptaSenior Manager Pharma Synth Formulations LimitedWe have been using Kubernetes cluster on E2E Cloud and are reasonably satisfied with its performance We were able to reduce our costs by 40 after migrating from Azure My big thanks to the E2E Cloud team for launching a Cloud and helping Indian startups in reducing their cloud costsAmarjeet SinghCoFounder CTO ZenatixThe platform is comfortable support is good 2 years anniversary completed in E2EMr Yonti LevinCoFounder CTO at LooraAbout UsE2E Networks Ltd is an Indiafocused Cloud Computing Company pioneering the introduction of contractless cloud computing for Indian startups and SMEs The E2E Networks Cloud has been employed by numerous successfully scaledup startups such as Zomato Cardekho Healthkart Junglee Games 1mg and many others It played a crucial role in facilitating their growth from the startup stage to achieving multimillion Daily Active Users DAUsLearn MoreWhat Our Customers SayFor over a decade we have delighted our customers with stellar infrastructure and supportI recently signed up with E2E Networks for their Cloud Server services and I have been very impressed with their Linux servers The service is not only very affordable but it also offers great performance and reliability I would highly recommend E2E Networks to anyone looking for a reliable and costeffective cloud server provider especially for Indian clients Proud WadhwaDjango Developer Great Future Technology Pvt LtdPress and Media MentionsListed on NSE Emerge Backed by Blume Ventures Loved by PressFrequently Asked QuestionsWhats the graphics memory of Nvidia V100 32 GBHow is the monthly pricing calculated Monthly prices shown are calculated using an assumed usage of 730 hours per month actual monthly costs may vary based on the number of days in a month Build on the most powerful infrastructure cloudGet Started for FreeContact SalesProductsCPU Intensive CloudHigh Memory CloudLinux Smart DedicatedcPanel Linux CloudWindows CloudWindows SQL CloudPlesk Windows CloudGPU Smart DedicatedLoad BalancerCompanyAbout UsMeet the TeamBecome a PartnerE2E in MediaTestimonialsInvestorsCareersContact UsContact SalesEscalation MatrixService Level AgreementTerms of ServicePrivacy PolicyRefund PolicyPolicy FAQResourcesBlogEventsService Health StatusHelpWhitePapersEcosystem EnablersCustomersCertificationsCountries ServedFAQsE2E CloudE2E Networks Limited is Indias fastest growing accelerated cloud computing playerSubscribe to our newsletterGet latest news articles resources and trends delivered to your inbox weeklyThank you Your submission has been receivedOops Something went wrong while submitting the 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E2E Networks Customer Validation Process for Indian Customers E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction How to Create EQS Actions Add Queue under tab Actions for queue service Using SDK Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS How to Create Functions Functions Information Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group How to create Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registry Simplifying Pull Operations with UserFriendly Interface API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation SignUp Process and Myaccount Dashboard Access E2E Networks Customer Validation Process for Indian Customers E2E Networks Customer Validation Process for Indian Customers In line with the recent CERTIn directions issued by Indian Computer Emergency Response Team CERTIn under subsection 6 of section 70B of the Information Technology Act 2000 relating to information security practices procedure prevention response and reporting of cyber incidents for Safe Trusted Internet dated April 28 2022 available at link httpswwwcertinorginPDFCERTInDirections70B28042022pdf the Data Centres Virtual Private Server VPS providers Cloud Service providers shall be required to inter alia maintain the validated contact details name and addresses of their subscribers Accordingly at least one contact in your myaccount CRN Customer Relationship Number needs to complete our Customer Validation process maximum by December 31 2022 by following the below mentioned steps If you are a PrimaryAdmin User in your CRN A primaryadmin user can themselves complete customer validation for the CRN using Click here or they can also nominate other users in the CRN to complete the customer validation process using Nominate When primaryadmin user clicks on nominate link in the Notification banner message then they will be redirected to the customer validation section under manage customer profile page Click on the nominate button towards the right of the specific user email to nominate that user to complete customer validation The nominated user will receive an email along with Notification banner message in their MyAccount login Nominated users can complete customer validation using click here link in the Notification banner message in the my account login Once a nominated user or primaryadmin user proceeds to do customer validation by using Click here in the banner message shown to them then they will need to accept the Term of Service TOS You need to tick the check box and Click on Agree and Proceed to proceed further Once you accept the Term of Service then you will be redirected to our identity verification partner who is asking your permission to allow them to get your details from Govt authorized databases to perform eKYC Note Please note we do not receive or store your complete 12digit Aadhaar number anywhere on the E2E Networks Limited servers We only retain limited data which can suffice to prove that the account was successfully validated Please rest assured that the information you have supplied will only be used for the purposes of validating the customer Click on Proceed to Digilocker when the following page appears Click on Allow Enter your Aadhaar and captcha and click on next Enter the otp received on your mobile number and click on continue Thereafter the following page will appear After a few seconds you will be redirected to your E2E Myaccount and a message that your customer validation is successfully completed will be shown If you are not a PrimaryAdmin User in your CRN You need to connect with your adminprimary user to complete customer validation or nominate youother users in your CRN to complete customer validation process On this page If you are a PrimaryAdmin User in your CRN If you are not a PrimaryAdmin User in your CRN Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited


How to set up Infra credits balance alert E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction How to Create EQS Actions Add Queue under tab Actions for queue service Using SDK Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS How to Create Functions Functions Information Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group How to create Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registry Simplifying Pull Operations with UserFriendly Interface API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation E2E Networks Billing and Payment Information How to set up Infra credits balance alert How to set up Infra credits balance alert Infra Credits Balance Alert You can set up an Infra Credits Balance alert that will be triggered via email or SMS when your infra credit balance falls below a threshold limit set by you Setting up Infra Credits Balance alert helps you to keep track of infra credits balance and avoid any surprises when you have overspent the Infra Credits or the balance goes to negative This feature is especially useful as an early warning system if someone launches surplus services by mistake It sends timely reminders to you to topup MyAccount with Infra Credits This is a standalone feature available under the AutoPay page and does not require you to add a credit or debit card You can follow the below steps to set up an Infra credit alert for your MyAccount STEP 1 Logging into E2E Networks My Account In your web browsers address bar type httpswwwe2enetworkscom Log in using your credentials set up at the time of creating and activating the E2E Networks MyAccount STEP 2 Navigate to PayNow page You see a Dashboard on your screen Click on the AutoPay submenu under the Billing heading on the left The AutoPay page will open on the right side STEP 3 Set up Infra Credits Balance Alert The Infra credits Balance alert is default enabled with 1000 threshold for your MyAccount To change the threshold value enter the new threshold value in the text box below This value is the lower watermark and if your infra credit balance falls below this value you will receive an alert on your preferred communication channel By default you will receive emailbased low Infra Credits Balance alert The SMS based alert mode is optional After selecting your preferred mode please click on Save You can change the threshold value and your preference for EmailSMS anytime later Also at any time you can optout to receive an infra credit balance alert by deselecting the checkbox On this page Infra Credits Balance Alert STEP 1 Logging into E2E Networks My Account STEP 2 Navigate to PayNow page STEP 3 Set up Infra Credits Balance Alert Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited