You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Q:

Enabling SSL on Kafka

I'm trying to connect to a kafka cluster with SSL required on brokers for clients to connect. Most clients can communicate with the brokers over SSL, so I know the brokers are set up correctly. We intent to use 2-way SSL authentication and followed these instructions: https://docs.confluent.io/current/tutorials/security_tutorial.html#security-tutorial.
However I have a java application that I'd like to connect to the brokers. I think SSL handshake is not complete and as a result the request to the broker is timing out. The same java application can connect to non-SSL enabled Kafka brokers without an issue.
Update:
I run into this when I tried to enable ssl. While debugging, authentication exception turned is null. I can also see that my truststore and keystore are loaded appropriately. So how do I troubleshoot this metadata update request timeout further? 
org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms.

From 
private ClusterAndWaitTime waitOnMetadata(String topic, Integer partition, long maxWaitMs) throws InterruptedException {

When I run kafka console producer using bitnami docker image with the same trustStore/keyStore passed as env variables, it works fine. 
This works: 
docker run -it -v /Users/kafka/kafka_2.11-1.0.0/bin/kafka.client.keystore.jks:/tmp/keystore.jks -v /Users/kafka/kafka_2.11-1.0.0/bin/kafka.client.truststore.jks:/tmp/truststore.jks -v /Users/kafka/kafka_2.11-1.0.0/bin/client_ssl.properties:/tmp/client.properties bitnami/kafka:1.0.0-r3 kafka-console-producer.sh --broker-list some-elb.elb.us-west-2.amazonaws.com:9094 --topic test --producer.config /tmp/client.properties

Here are the debug logs from my java client application. Appreciate any insight on how to troubleshoot this.
                2018-03-13 20:13:38.661  INFO 20653 --- [           main] s.b.c.e.t.TomcatEmbeddedServletContainer : Tomcat started on port(s): 8080 (http)
2018-03-13 20:13:38.669  INFO 20653 --- [           main] c.i.aggregate.precompute.Application     : Started Application in 14.066 seconds (JVM running for 15.12)
2018-03-13 20:13:42.225  INFO 20653 --- [           main] o.a.k.clients.producer.ProducerConfig    : ProducerConfig values: 
    acks = all
    batch.size = 16384
    bootstrap.servers = [some-elb.elb.us-west-2.amazonaws.com:9094]
    buffer.memory = 33554432
    client.id = 
    compression.type = lz4
    connections.max.idle.ms = 540000
    enable.idempotence = false
    interceptor.classes = null
    key.serializer = class org.apache.kafka.common.serialization.StringSerializer
    linger.ms = 0
    max.block.ms = 2000
    max.in.flight.requests.per.connection = 5
    max.request.size = 1048576
    metadata.max.age.ms = 300000
    metric.reporters = []
    metrics.num.samples = 2
    metrics.recording.level = INFO
    metrics.sample.window.ms = 30000
    partitioner.class = class org.apache.kafka.clients.producer.internals.DefaultPartitioner
    receive.buffer.bytes = 32768
    reconnect.backoff.max.ms = 1000
    reconnect.backoff.ms = 50
    request.timeout.ms = 30000
    retries = 2147483647
    retry.backoff.ms = 100
    sasl.jaas.config = null
    sasl.kerberos.kinit.cmd = /usr/bin/kinit
    sasl.kerberos.min.time.before.relogin = 60000
    sasl.kerberos.service.name = null
    sasl.kerberos.ticket.renew.jitter = 0.05
    sasl.kerberos.ticket.renew.window.factor = 0.8
    sasl.mechanism = GSSAPI
    security.protocol = SSL
    send.buffer.bytes = 131072
    ssl.cipher.suites = null
    ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
    ssl.endpoint.identification.algorithm = null
    ssl.key.password = [hidden]
    ssl.keymanager.algorithm = SunX509
    ssl.keystore.location = /Users/kafka/Cluster-Certs/kafka.client.keystore.jks
    ssl.keystore.password = [hidden]
    ssl.keystore.type = JKS
    ssl.protocol = TLS
    ssl.provider = null
    ssl.secure.random.implementation = null
    ssl.trustmanager.algorithm = PKIX
    ssl.truststore.location = /Users/kafka/Cluster-Certs/kafka.client.truststore.jks
    ssl.truststore.password = [hidden]
    ssl.truststore.type = JKS
    transaction.timeout.ms = 60000
    transactional.id = null
    value.serializer = <some class>

2018-03-13 20:13:42.287 TRACE 20653 --- [           main] o.a.k.clients.producer.KafkaProducer     : [Producer clientId=producer-1] Starting the Kafka producer
2018-03-13 20:13:42.841 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name bufferpool-wait-time
2018-03-13 20:13:43.062 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name buffer-exhausted-records
2018-03-13 20:13:43.217 DEBUG 20653 --- [           main] org.apache.kafka.clients.Metadata        : Updated cluster metadata version 1 to Cluster(id = null, nodes = [some-elb.elb.us-west-2.amazonaws.com:9094 (id: -1 rack: null)], partitions = [])
2018-03-13 20:13:45.670 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name produce-throttle-time
2018-03-13 20:13:45.909 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name connections-closed:
2018-03-13 20:13:45.923 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name connections-created:
2018-03-13 20:13:45.935 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name successful-authentication:
2018-03-13 20:13:45.946 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name failed-authentication:
2018-03-13 20:13:45.958 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name bytes-sent-received:
2018-03-13 20:13:45.968 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name bytes-sent:
2018-03-13 20:13:45.990 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name bytes-received:
2018-03-13 20:13:46.005 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name select-time:
2018-03-13 20:13:46.025 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name io-time:
2018-03-13 20:13:46.130 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name batch-size
2018-03-13 20:13:46.139 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name compression-rate
2018-03-13 20:13:46.147 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name queue-time
2018-03-13 20:13:46.156 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name request-time
2018-03-13 20:13:46.165 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name records-per-request
2018-03-13 20:13:46.179 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name record-retries
2018-03-13 20:13:46.189 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name errors
2018-03-13 20:13:46.199 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name record-size
2018-03-13 20:13:46.250 DEBUG 20653 --- [           main] org.apache.kafka.common.metrics.Metrics  : Added sensor with name batch-split-rate
2018-03-13 20:13:46.275 DEBUG 20653 --- [ad | producer-1] o.a.k.clients.producer.internals.Sender  : [Producer clientId=producer-1] Starting Kafka producer I/O thread.
2018-03-13 20:13:46.329  INFO 20653 --- [           main] o.a.kafka.common.utils.AppInfoParser     : Kafka version : 1.0.0
2018-03-13 20:13:46.333  INFO 20653 --- [           main] o.a.kafka.common.utils.AppInfoParser     : Kafka commitId : aaa7af6d4a11b29d
2018-03-13 20:13:46.369 DEBUG 20653 --- [           main] o.a.k.clients.producer.KafkaProducer     : [Producer clientId=producer-1] Kafka producer started
2018-03-13 20:13:52.982 TRACE 20653 --- [           main] o.a.k.clients.producer.KafkaProducer     : [Producer clientId=producer-1] Requesting metadata update for topic ssl-txn.
2018-03-13 20:13:52.987 TRACE 20653 --- [ad | producer-1] org.apache.kafka.clients.NetworkClient   : [Producer clientId=producer-1] Found least loaded node some-elb.elb.us-west-2.amazonaws.com:9094 (id: -1 rack: null)
2018-03-13 20:13:52.987 DEBUG 20653 --- [ad | producer-1] org.apache.kafka.clients.NetworkClient   : [Producer clientId=producer-1] Initialize connection to node some-elb.elb.us-west-2.amazonaws.com:9094 (id: -1 rack: null) for sending metadata request
2018-03-13 20:13:52.987 DEBUG 20653 --- [ad | producer-1] org.apache.kafka.clients.NetworkClient   : [Producer clientId=producer-1] Initiating connection to node some-elb.elb.us-west-2.amazonaws.com:9094 (id: -1 rack: null)
2018-03-13 20:13:53.217 DEBUG 20653 --- [ad | producer-1] org.apache.kafka.common.metrics.Metrics  : Added sensor with name node--1.bytes-sent
2018-03-13 20:13:53.219 DEBUG 20653 --- [ad | producer-1] org.apache.kafka.common.metrics.Metrics  : Added sensor with name node--1.bytes-received
2018-03-13 20:13:53.219 DEBUG 20653 --- [ad | producer-1] org.apache.kafka.common.metrics.Metrics  : Added sensor with name node--1.latency
2018-03-13 20:13:53.222 DEBUG 20653 --- [ad | producer-1] o.apache.kafka.common.network.Selector   : [Producer clientId=producer-1] Created socket with SO_RCVBUF = 33488, SO_SNDBUF = 131376, SO_TIMEOUT = 0 to node -1
2018-03-13 20:13:53.224 TRACE 20653 --- [ad | producer-1] o.a.k.common.network.SslTransportLayer   : SSLHandshake NEED_WRAP channelId -1, appReadBuffer pos 0, netReadBuffer pos 0, netWriteBuffer pos 0
2018-03-13 20:13:53.224 TRACE 20653 --- [ad | producer-1] o.a.k.common.network.SslTransportLayer   : SSLHandshake handshakeWrap -1
2018-03-13 20:13:53.225 TRACE 20653 --- [ad | producer-1] o.a.k.common.network.SslTransportLayer   : SSLHandshake NEED_WRAP channelId -1, handshakeResult Status = OK HandshakeStatus = NEED_UNWRAP
bytesConsumed = 0 bytesProduced = 326, appReadBuffer pos 0, netReadBuffer pos 0, netWriteBuffer pos 0
2018-03-13 20:13:53.226 TRACE 20653 --- [ad | producer-1] o.a.k.common.network.SslTransportLayer   : SSLHandshake NEED_UNWRAP channelId -1, appReadBuffer pos 0, netReadBuffer pos 0, netWriteBuffer pos 326
2018-03-13 20:13:53.226 TRACE 20653 --- [ad | producer-1] o.a.k.common.network.SslTransportLayer   : SSLHandshake handshakeUnwrap -1
2018-03-13 20:13:53.227 TRACE 20653 --- [ad | producer-1] o.a.k.common.network.SslTransportLayer   : SSLHandshake handshakeUnwrap: handshakeStatus NEED_UNWRAP status BUFFER_UNDERFLOW
2018-03-13 20:13:53.227 TRACE 20653 --- [ad | producer-1] o.a.k.common.network.SslTransportLayer   : SSLHandshake NEED_UNWRAP channelId -1, handshakeResult Status = BUFFER_UNDERFLOW HandshakeStatus = NEED_UNWRAP
bytesConsumed = 0 bytesProduced = 0, appReadBuffer pos 0, netReadBuffer pos 0, netWriteBuffer pos 326
2018-03-13 20:13:53.485 DEBUG 20653 --- [ad | producer-1] org.apache.kafka.clients.NetworkClient   : [Producer clientId=producer-1] Completed connection to node -1. Fetching API versions.
2018-03-13 20:13:53.485 TRACE 20653 --- [ad | producer-1] org.apache.kafka.clients.NetworkClient   : [Producer clientId=producer-1] Found least loaded node some-elb.elb.us-west-2.amazonaws.com:9094 (id: -1 rack: null)
2018-03-13 20:13:54.992 DEBUG 20653 --- [           main] o.a.k.clients.producer.KafkaProducer     : [Producer clientId=producer-1] Exception occurred during message send:

org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 2000 ms.

2018-03-13 20:13:54.992  INFO 20653 --- [           main] c.i.aggregate.precompute.kafka.Producer  : sent message in callback 
java.util.concurrent.ExecutionException: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 2000 ms.
    at org.apache.kafka.clients.producer.KafkaProducer$FutureFailure.<init>(KafkaProducer.java:1124)
    at org.apache.kafka.clients.producer.KafkaProducer.doSend(KafkaProducer.java:823)
    at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:760)
    at com.intuit.aggregate.precompute.kafka.Producer.send(Producer.java:76)
    at com.intuit.aggregate.precompute.Application.main(Application.java:58)
Caused by: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 2000 ms.
Disconnected from the target VM, address: '127.0.0.1:53161', transport: 'socket'

A:

This issue was due to an incorrect cert on brokers. java has different defaults than scala/python, for the ciphers which is why other language clients worked. But go also had a similar issue and then they enabled ssl logging on brokers and caught the issue.