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Optimize write throughput for Amazon Kinesis Data Streams

AWS Big Data

We then guide you on swift responses to these events and provide several solutions for mitigation. Imagine you have a fleet of web servers logging performance metrics for each web request served into a Kinesis data stream with two shards and you used a request URL as the partition key. Why do we get write throughput exceeded errors?

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. The data quality analysis metrics of complete and accurate data are imperative to this step. Table of Contents. 2) Why Do You Need DQM?

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Enable cost-efficient operational analytics with Amazon OpenSearch Ingestion

AWS Big Data

Although this walkthrough uses VPC flow log data, the same pattern applies for use with AWS CloudTrail , Amazon CloudWatch , any log files as well as any OpenTelemetry events, and custom producers. Create an S3 bucket for storing archived events, and make a note of S3 bucket name. Set up an OpenSearch Service domain.

Analytics 121
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Ingest, transform, and deliver events published by Amazon Security Lake to Amazon OpenSearch Service

AWS Big Data

When it comes to near-real-time analysis of data as it arrives in Security Lake and responding to security events your company cares about, Amazon OpenSearch Service provides the necessary tooling to help you make sense of the data found in Security Lake. Services such as Amazon Athena and Amazon SageMaker use query access.

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Safely remove Kafka brokers from Amazon MSK provisioned clusters

AWS Big Data

Administrators can optimize the costs of their Amazon MSK clusters by reducing broker count and adapting the cluster capacity to the changes in the streaming data demand, without affecting their clusters’ performance, availability, or data durability. Alternatively, you may have brokers that are not hosting any partitions.

Metrics 74
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Scale AWS Glue jobs by optimizing IP address consumption and expanding network capacity using a private NAT gateway

AWS Big Data

In this post, we will discuss two strategies to scale AWS Glue jobs: Optimizing the IP address consumption by right-sizing Data Processing Units (DPUs), using the Auto Scaling feature of AWS Glue, and fine-tuning of the jobs. Now let us look at the first solution that explains optimizing the AWS Glue IP address consumption. Click next.

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How to achieve Kubernetes observability: Principles and best practices

IBM Big Data Hub

Observability comprises a range of processes and metrics that help teams gain actionable insights into a system’s internal state by examining system outputs. In this blog, we discuss how Kubernetes observability works, and how organizations can use it to optimize cloud-native IT architectures. How does observability work?

Metrics 67