Flaky tests are bad—this is a fact implicitly understood by developers, platform and DevOps engineers, and SREs alike. When tests flake (i.e., generate conflicting results across test runs, without any changes to the code or test), they can arbitrarily fail builds, requiring developers to re-run the test or the full pipeline. This process can take hours—especially for large or monolithic repositories—and slow down the software delivery cycle.

Azure OpenAI Service is Microsoft’s fully managed platform for deploying generative AI services powered by OpenAI. Azure OpenAI Service provides access to models including GPT-4o, GPT-4o mini, GPT-4 Turbo with Vision, DALLE-3, and the Embeddings model series, alongside the enterprise security, governance, and infrastructure capabilities of Azure.

Logs are a rich source of information, providing you with the minute details you need to troubleshoot a specific issue or perform extensive historical analysis. But with billions of logs being generated from your infrastructure every day, it isn’t practical to sift through them all to derive actionable insights. Firewall, CDN, network activity, and load balancer logs are especially high volume, requiring storage solutions that can be expensive and difficult to scale.

AWS enables customers to retry or redrive Step Functions executions to continue any failed executions of Standard Workflows from their points of failure while maintaining all inputs. For example, if you find broken downstream logic in your code or experience unexpected errors upon execution, you can remediate those errors by fully re-running an execution or use redrive to continue this execution.

Camunda 8 is a process orchestration platform that automates and executes business processes at scale. Many organizations orchestrate their business processes using Camunda 8 Self-Managed because it can operate in their preferred public cloud provider, such as AWS, or in a private cloud, like a Kubernetes cluster. However, hosting Camunda 8 while maintaining its health and performance will require complete visibility into your environment, helping you properly allocate resources and minimize downtime.

A memory leak is a faulty condition where a program fails to free up memory it no longer needs. If left unaddressed, memory leaks result in ever-increasing memory usage, which in turn can lead to degraded performance, system instability, and application crashes. Most modern programming languages include a built-in mechanism to protect against this problem, with garbage collection being the most common. Go has a garbage collector (GC) that does a very good job of managing memory.

Like most organizations, we are always trying to be as efficient as possible in our usage of our cloud resources. To help accomplish this, we encourage individual engineering teams at Datadog to look for opportunities to optimize. They can share their performance wins, big or small, in an internal Slack channel along with visualizations and, often, calculations of the resulting annual cost savings.

Managing your AWS costs is both crucial and complex, and as your AWS environment grows, it becomes harder to know where you can optimize and how to execute the necessary changes. Datadog Cloud Cost Management provides invaluable visibility into your cloud spend that enables you to explore costs and investigate trends that impact your cloud bill.