cwielenb/CNCF-Dataset huggingface dataset:
Project: kube-hunter (Provisioning / Security & Compliance)
File: KHV043.md

vid: KHV043 title: Cluster Health Disclosure categories: [Information Disclosure] severity: low The kubelet is leaking it's health information, which may contain sensitive information, via the `/healthz` endpoint. This endpoint is exposed as part of the kubelet's debug handlers. Disable `--enable-debugging-handlers` kubelet flag.
Project: Chef InSpec (Provisioning / Security & Compliance)
File: google_compute_region_backend_services.md

+++ title = "googlecomputeregionbackendservices resource" draft = false gh_repo = "inspec" platform = "gcp" [menu] [menu.inspec] title = "googlecomputeregionbackendservices" identifier = "inspec/resources/gcp/googlecomputeregionbackendservices.md googlecomputeregionbackendservices resource" parent = "inspec/resources/gcp" +++ A `googlecomputeregionbackendservices` is used to test a Google RegionBackendService resource This resource has beta fields available. To retrieve these fields, include `beta: true` in the constructor for the resource ```ruby describe googlecomputeregionbackendservices(project: 'chef-gcp-inspec', region: 'europe-west2') do its('count') { should be >= 1 } its('names') { should include 'inspec-gcp-region-backend-service' } its('protocols') { should include 'TCP' } its('timeout_secs') { should include '15' } end ``` Properties that can be accessed from the `googlecomputeregionbackendservices` resource: See the resource for more information. `affinitycookiettl_secs` : an array of `googlecomputeregionbackendservice` affinitycookiettl_sec `backends` : an array of `googlecomputeregionbackendservice` backends `circuit_breakers` : an array of `googlecomputeregionbackendservice` circuit_breakers `consistent_hashes` : an array of `googlecomputeregionbackendservice` consistent_hash `connection_drainings` : an array of `googlecomputeregionbackendservice` connection_draining `creation_timestamps` : an array of `googlecomputeregionbackendservice` creation_timestamp `descriptions` : an array of `googlecomputeregionbackendservice` description `failover_policies` : an array of `googlecomputeregionbackendservice` failover_policy `fingerprints` : an array of `googlecomputeregionbackendservice` fingerprint `health_checks` : an array of `googlecomputeregionbackendservice` health_checks `ids` : an array of `googlecomputeregionbackendservice` id `loadbalancingschemes` : an array of `googlecomputeregionbackendservice` loadbalancingscheme `localitylbpolicies` : an array of `googlecomputeregionbackendservice` localitylbpolicy `names` : an array of `googlecomputeregionbackendservice` name `outlier_detections` : an array of `googlecomputeregionbackendservice` outlier_detection `port_names` : an array of `googlecomputeregionbackendservice` port_name `protocols` : an array of `googlecomputeregionbackendservice` protocol `session_affinities` : an array of `googlecomputeregionbackendservice` session_affinity `timeout_secs` : an array of `googlecomputeregionbackendservice` timeout_sec `log_configs` : an array of `googlecomputeregionbackendservice` log_config `networks` : an array of `googlecomputeregionbackendservice` network `regions` : an array of `googlecomputeregionbackendservice` region This resource supports all of the above properties as filter criteria, which can be used with `where` as a block or a method. Ensure the is enabled for the current project.
Project: YugabyteDB (App Definition and Development / Database)
File: dcl_drop_group.md

title: DROP GROUP statement [YSQL] linkTitle: DROP GROUP description: Use the DROP GROUP statement to drop a role. DROP GROUP is an alias for DROP ROLE and is used to drop a role. menu: v2.18: identifier: dcldropgroup parent: statements type: docs Use the `DROP GROUP` statement to drop a role. `DROP GROUP` is an alias for and is used to drop a role. {{%ebnf%}} drop_group {{%/ebnf%}} See for more details. Drop a group. ```plpgsql yugabyte=# DROP GROUP SysAdmin; ```
Project: Lagoon (App Definition and Development / Application Definition & Image Build)
File: other.md

Even if Lagoon doesn't have a base image for your particular application, framework or language, Lagoon can still build it! Extending on, or inheriting from the , Lagoon can run almost any workload. This brief example shows how to build a Hugo website and serve it as static files in an NGINX image. The commons image is used to add Hugo, copy the site in, and build it. The NGINX image is then used to serve the site, with the addition of a customized NGINX config. ```bash title="nginx.dockerfile" FROM uselagoon/commons as builder RUN apk add hugo git WORKDIR /app COPY . /app RUN hugo FROM uselagoon/nginx COPY --from=builder /app/public/ /app COPY lagoon/static-files.conf /etc/nginx/conf.d/app.conf RUN fix-permissions /usr/local/openresty/nginx ``` ```yaml title="docker-compose.yml" services: nginx: build: context: . dockerfile: lagoon/nginx.Dockerfile labels: lagoon.type: nginx ```
Project: TDengine (App Definition and Development / Database)
File: 03-tolerance.md

title: Fault Tolerance and Disaster Recovery description: This document describes how TDengine provides fault tolerance and disaster recovery. TDengine uses WAL, i.e. Write Ahead Log, to achieve fault tolerance and high reliability. When a data block is received by TDengine, the original data block is first written into WAL. The log in WAL will be deleted only after the data has been written into data files in the database. Data can be recovered from WAL in case the server is stopped abnormally for any reason and then restarted. There are 2 configuration parameters related to WAL: wal_level: Specifies the WAL level. 1 indicates that WAL is enabled but fsync is disabled. 2 indicates that WAL and fsync are both enabled. The default value is 1. walfsyncperiod: This parameter is only valid when wal_level is set to 2. It specifies the interval, in milliseconds, of invoking fsync. If set to 0, it means fsync is invoked immediately once WAL is written. To achieve absolutely no data loss, set wallevel to 2 and walfsyncperiod to 0. There is a performance penalty to the data ingestion rate. However, if the concurrent data insertion threads on the client side can reach a big enough number, for example 50, the data ingestion performance will be still good enough. Our verification shows that the drop is only 30% when walfsync_period is set to 3000 milliseconds. TDengine provides disaster recovery by using taosX to replicate data between two TDengine clusters which are deployed in two distant data centers. Assume there are two TDengine clusters, A and B, A is the source and B is the target, and A takes the workload of writing and querying. You can deploy `taosX` in the data center where cluster A resides in, `taosX` consumes the data written into cluster A and writes into cluster B. If the data center of cluster A is disrupted because of disaster, you can switch to cluster B to take the workload of data writing and querying, and deploy a `taosX` in the data center of cluster B to replicate data from cluster B to cluster A if cluster A has been recovered, or another cluster C if cluster A has not been recovered. You can use the data replication feature of `taosX` to build more complicated disaster recovery solution. taosX is only provided in TDengine enterprise edition, for more details please contact business@tdengine.com.
Project: Beam (App Definition and Development / Streaming & Messaging)
File: veepee.md

title: "Veepee" icon: /images/logos/powered-by/veepee.png hasLink: "https://fr.veepee.be/vexbridge/" <!-- Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. -->
Project: Beam (App Definition and Development / Streaming & Messaging)
File: kafka-to-pubsub-example.md

layout: post title: "Example to ingest data from Apache Kafka to Google Cloud Pub/Sub" date: 2021-01-15 00:00:01 -0800 categories: blog java authors: arturkhanin ilyakozyrev alexkosolapov <!-- Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> In this blog post we present an example that creates a pipeline to read data from a single topic or multiple topics from and write data into a topic in . The example provides code samples to implement simple yet powerful pipelines and also provides an out-of-the-box solution that you can just _" plug'n'play"_. This end-to-end example is included in and can be downloaded . We hope you will find this example useful for setting up data pipelines between Kafka and Pub/Sub. Supported data formats: Serializable plain text formats, such as JSON Supported input source configurations: Single or multiple Apache Kafka bootstrap servers Apache Kafka SASL/SCRAM authentication over plaintext or SSL connection Secrets vault service Supported destination configuration: Single Google Pub/Sub topic In a simple scenario, the example will create an Apache Beam pipeline that will read messages from a source Kafka server with a source topic, and stream the text messages into specified Pub/Sub destination topic. Other scenarios may need Kafka SASL/SCRAM authentication, that can be performed over plaintext or SSL encrypted connection. The example supports using a single Kafka user account to authenticate in the provided source Kafka servers and topics. To support SASL authentication over SSL the example will need an SSL certificate location and access to a secrets vault service with Kafka username and password, currently supporting HashiCorp Vault. There are two ways to execute the pipeline. Locally. This way has many options - run directly from your IntelliJ, or create `.jar` file and run it in the terminal, or use your favourite method of running Beam pipelines. In using Google Cloud : With `gcloud` command-line tool you can create a out of this Beam example and execute it in Google Cloud Platform. _This requires corresponding modifications of the example to turn it into a template._ This example exists as a within repository and can be run with no additional code modifications. Give this Beam end-to-end example a try. If you are new to Beam, we hope this example will give you more understanding on how pipelines work and look like. If you are already using Beam, we hope some code samples in it will be useful for your use cases. Please if you encounter any issues.
Project: Meshery (Provisioning / Automation & Configuration)
File: 10-01-2022-03-13-10_6f9b5f55.md

timestamp: "2022-10-01 03:12:55 UTC Sat" meshery-component: meshery-consul meshery-component-version: edge meshery-server-version: "v0.6.9" k8s-distro: minikube k8s-version: "v1.23.9" service-mesh: Consul service-mesh-version: "v0.49.0" tests: consul-client: null consul-server: null overall-status: "failing"
Project: ClickHouse (App Definition and Development / Database)
File: v22.8.21.38-lts.md

sidebar_position: 1 sidebar_label: 2023 Backported in : Packing inline cache into docker images sometimes causes strange special effects. Since we don't use it at all, it's good to go. (). Backported in : Preserve environment parameters in `clickhouse start` command. Fixes . (). Fix Block structure mismatch in Pipe::unitePipes for FINAL (). Fix ORDER BY tuple of WINDOW functions (). Fix `countSubstrings()` hang with empty needle and a column haystack (). The implementation of AnyHash was non-conformant. (). init and destroy ares channel on demand.. (). clickhouse-keeper: fix implementation of server with poll() (). Not-ready Set (). Fix incorrect normal projection AST format (). Fix: interpolate expression takes source column instead of same name aliased from select expression. (). Correctly handle totals and extremes with `DelayedSource` (). Fix: sorted distinct with sparse columns (). Fix crash in comparison functions due to incorrect query analysis (). Fix deadlocks in StorageTableFunctionProxy (). Disable testreversedns_query/test.py (). Disable testhostregexpmultipleptr_records/test.py (). Fix broken `02862sorteddistinctsparsefix` (). Get rid of describe_parameters for the best robot token ().
Project: ClickHouse (App Definition and Development / Database)
File: topk.md

slug: /en/sql-reference/aggregate-functions/reference/topk sidebar_position: 108 Returns an array of the approximately most frequent values in the specified column. The resulting array is sorted in descending order of approximate frequency of values (not by the values themselves). Implements the algorithm for analyzing TopK, based on the reduce-and-combine algorithm from . ``` sql topK(N)(column) topK(N, load_factor)(column) topK(N, load_factor, 'counts')(column) ``` This function does not provide a guaranteed result. In certain situations, errors might occur and it might return frequent values that arent the most frequent values. We recommend using the `N < 10` value; performance is reduced with large `N` values. Maximum value of `N = 65536`. Parameters `N` The number of elements to return. Optional. Default value: 10. `loadfactor` Defines, how many cells reserved for values. If uniq(column) > N * loadfactor, result of topK function will be approximate. Optional. Default value: 3. `counts` Defines, should result contain approximate count and error value. Arguments `column` The value to calculate frequency. Example Take the data set and select the three most frequently occurring values in the `AirlineID` column. ``` sql SELECT topK(3)(AirlineID) AS res FROM ontime ``` ``` text res [19393,19790,19805] ``` See Also
Project: YugabyteDB (App Definition and Development / Database)
File: remove-operators.md

title: "- and #- (remove operators) [JSON]" headerTitle: "- and #- (remove operators)" linkTitle: "- and #- (remove)" description: Remove key-value pairs from an object or remove a single value from an array. menu: v2.18: identifier: remove-operators parent: json-functions-operators weight: 13 type: docs Purpose: Remove key-value pairs from an object or a single value from an array. The plain `-` variant takes the specified object itself. The `#-` variant takes the path from the specified object. Notes: Describing the behavior by using the term "remove" is a convenient shorthand. The actual effect of these operators is to create a new `jsonb` value from the specified `jsonb` value according to the rule that the operator implements, parameterized by the SQL value on the right of the operator. Purpose: Remove key-value pairs from an object or a single value from an array. Signature: ``` input values: jsonb - [int | text] return value: jsonb ``` Notes: There is no `json` overload. To remove a single key-value pair: ```plpgsql do $body$ declare j_left constant jsonb := '{"a": "x", "b": "y"}'; key constant text := 'a'; j_expected constant jsonb := '{"b": "y"}'; begin assert jleft - key = jexpected, 'unexpected'; end; $body$; ``` To remove several key-value pairs: ```plpgsql do $body$ declare j_left constant jsonb := '{"a": "p", "b": "q", "c": "r"}'; key_list constant text[] := array['a', 'c']; j_expected constant jsonb := '{"b": "q"}'; begin assert jleft - keylist = j_expected, 'unexpected'; end; $body$; ``` To remove a single value from an array: ```plpgsql do $body$ declare j_left constant jsonb := '[1, 2, 3, 4]'; idx constant int := 0; j_expected constant jsonb := '[2, 3, 4]'; begin assert jleft - idx = jexpected, 'unexpected'; end; $body$; ``` There is no direct way to remove several values from an array at a list of indexes, analogous to the ability to remove several key-value pairs from an object with a list of pair keys. The obvious attempt fails with this error: ``` operator does not exist: jsonb - integer[] ``` You can achieve the result thus: ```plpgsql do $body$ declare j_left constant jsonb := '[1, 2, 3, 4, 5, 7]'; idx constant int := 0; j_expected constant jsonb := '[4, 5, 7]'; begin assert ((jleft - idx) - idx) - idx = jexpected, 'unexpected'; end; $body$; ``` Purpose: Remove a single key-value pair from an object or a single value from an array at the specified path. Signature: ``` input values: jsonb - text[] return value: jsonb ``` Notes: There is no `json` overload. ```plpgsql do $body$ declare j_left constant jsonb := '["a", {"b":17, "c": ["dog", "cat"]}]'; path constant text[] := array['1', 'c', '0']; j_expected constant jsonb := '["a", {"b": 17, "c": ["cat"]}]'; begin assert jleft #- path = jexpected, 'assert failed'; end; $body$; ``` Just as with the , array index values are presented as convertible `text` values. Notice that the address of each JSON array element along the path is specified JSON-style, where the index starts at zero.
Project: FOSSA (Provisioning / Security & Compliance)
File: cargo.md

Ideal/Minimum `cargo` buildtool installed on your machine `Cargo.toml` file present in your project Directories containing `Cargo.toml` files are considered cargo projects. Subdirectories of cargo projects are not re-scanned for nested cargo projects, because the dependency tree of the parent project already includes the dependency tree of those subprojects. To scan only the subprojects, run the `fossa` tool against the subproject directories
Project: YugabyteDB (App Definition and Development / Database)
File: yba_storage-config_gcs.md

Manage a YugabyteDB Anywhere GCS storage configuration Manage a GCS storage configuration in YugabyteDB Anywhere ``` yba storage-config gcs [flags] ``` ``` -n, --name string [Optional] The name of the storage configuration for the operation. Required for create, delete, describe, update. -h, --help help for gcs ``` ``` -a, --apiToken string YugabyteDB Anywhere api token. --config string Config file, defaults to $HOME/.yba-cli.yaml --debug Use debug mode, same as --logLevel debug. --disable-color Disable colors in output. (default false) -H, --host string YugabyteDB Anywhere Host (default "http://localhost:9000") -l, --logLevel string Select the desired log level format. Allowed values: debug, info, warn, error, fatal. (default "info") -o, --output string Select the desired output format. Allowed values: table, json, pretty. (default "table") --timeout duration Wait command timeout, example: 5m, 1h. (default 168h0m0s) --wait Wait until the task is completed, otherwise it will exit immediately. (default true) ``` - Manage YugabyteDB Anywhere storage configurations - Create a GCS YugabyteDB Anywhere storage configuration - Delete a GCS YugabyteDB Anywhere storage configuration - Describe a GCS YugabyteDB Anywhere storage configuration - List GCS YugabyteDB Anywhere storage-configurations - Update an GCS YugabyteDB Anywhere storage configuration
Project: Meshery (Provisioning / Automation & Configuration)
File: apisix-ingress-controller.md

layout: integration title: APISIX Ingress Controller subtitle: Collaborative and visual infrastructure as code for APISIX Ingress Controller image: /assets/img/integrations/apisix-ingress-controller/icons/color/apisix-ingress-controller-color.svg permalink: extensibility/integrations/apisix-ingress-controller docURL: https://docs.meshery.io/extensibility/integrations/apisix-ingress-controller description: integrations-category: Cloud Native Network integrations-subcategory: API Gateway registrant: Artifact Hub components: name: apisix-cluster-config colorIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-cluster-config/icons/color/apisix-cluster-config-color.svg whiteIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-cluster-config/icons/white/apisix-cluster-config-white.svg description: name: apisix-consumer colorIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-consumer/icons/color/apisix-consumer-color.svg whiteIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-consumer/icons/white/apisix-consumer-white.svg description: name: apisix-route colorIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-route/icons/color/apisix-route-color.svg whiteIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-route/icons/white/apisix-route-white.svg description: name: apisix-tls colorIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-tls/icons/color/apisix-tls-color.svg whiteIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-tls/icons/white/apisix-tls-white.svg description: name: apisix-upstream colorIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-upstream/icons/color/apisix-upstream-color.svg whiteIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-upstream/icons/white/apisix-upstream-white.svg description: name: apisix-plugin-config colorIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-plugin-config/icons/color/apisix-plugin-config-color.svg whiteIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-plugin-config/icons/white/apisix-plugin-config-white.svg description: name: apisix-global-rule colorIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-global-rule/icons/color/apisix-global-rule-color.svg whiteIcon: assets/img/integrations/apisix-ingress-controller/components/apisix-global-rule/icons/white/apisix-global-rule-white.svg description: featureList: [ "The Apache APISIX Dashboard is designed to make it as easy as possible for users to operate through a frontend interface.", "The Apache APISIX dashboard is flexible to User demands.", "Built-in and customizable plugins available." ] howItWorks: "Collaborative Infrastructure as Code" howItWorksDetails: "Collaboratively manage infrastructure with your coworkers synchronously sharing the same designs." language: en list: include type: extensibility category: integrations
Project: KICS (Provisioning / Security & Compliance)
File: ee305555-6b1d-4055-94cf-e22131143c34.md

title: PSP Set To Privileged hide: toc: true navigation: true <style> .highlight .hll { background-color: #ff171742; } .md-content { max-width: 1100px; margin: 0 auto; } </style> Query id: ee305555-6b1d-4055-94cf-e22131143c34 Query name: PSP Set To Privileged Platform: Pulumi Severity: <span style="color:#bb2124">High</span> Category: Insecure Configurations URL: Do not allow pod to request execution as privileged.<br> ```yaml title="Positive test num. 1 - yaml file" hl_lines="11" name: aws-eks runtime: yaml description: An EKS cluster resources: example: type: kubernetes:policy/v1beta1:PodSecurityPolicy properties: metadata: name: example spec: privileged: true ``` ```yaml title="Negative test num. 1 - yaml file" name: aws-eks runtime: yaml description: An EKS cluster resources: example: type: kubernetes:policy/v1beta1:PodSecurityPolicy properties: metadata: name: example spec: privileged: false ```
Project: EMQ Technologies (App Definition and Development / Streaming & Messaging)
File: fix-12802.en.md

Improve cluster discovery behaviour when a node is manually removed from a cluster using 'emqx ctl cluster leave' command. Previously, if the configured cluster 'discovery_strategy' was not 'manual', the left node might re-discover and re-join the same cluster shortly after it left (unless it was stopped). After this change, 'cluster leave' command disables automatic cluster_discovery, so that the left node won't re-join the same cluster again. Cluster discovery can be re-enabled by running 'emqx ctl discovery enable` or by restarting the left node.