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By Nicholas Thomson
As the number of distinct sources generating logs across systems and applications grows, teams face the challenge of normalizing log data at scale. This challenge can manifest when you’re simply looking to leverage logs “off-the-shelf” for investigations, dashboards, or reports–especially when you don’t control the content and structure of certain logs (like those collected from third-party applications and platforms).
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By Yanbing Li
We are thrilled to announce that Datadog has been named a Leader in the first ever 2024 Gartner Magic Quadrant for Digital Experience Monitoring. Datadog was positioned the highest in its Ability to Execute. We believe this placement reflects our commitment to being an end-to-end observability platform that brings together all signals from across your tech stack into a unified ecosystem.
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By Tushar Shrimali
As teams adopt OpenTelemetry (OTel) to instrument their systems in a vendor-neutral way, they often face a challenge in effectively tracing activity throughout their entire stack, from frontend user interactions to backend services and databases. While OTel enables basic tracing, teams still need a way to access advanced capabilities like continuous profiling to adequately optimize performance and troubleshoot issues in their applications.
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By Bowen Chen
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.
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By Thomas Sobolik
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.
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By Candace Shamieh
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.
Reduce your AWS Step Functions' error remediation time by redriving executions directly from Datadog
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By Jake Greenberg
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.
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By Candace Shamieh
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.
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By George Kampitakis
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.
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By Bowen Chen
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.
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By Datadog
Learn how Appfolio is delivering positive customer experiences in real estate with generative AI — supported and safeguarded by Datadog’s LLM Observability. See how you can use Datadog LLM Observability to monitor, troubleshoot, improve, and secure your LLM applications.
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By Datadog
Datadog is constantly elevating the approach to cloud monitoring and security. This Month in Datadog updates you on our newest product features, announcements, resources, and events. To learn more about Datadog and start a free 14-day trial, visit Cloud Monitoring as a Service | Datadog. This month, we put the Spotlight on Datadog LLM Observability’s native integration with Google Gemini.
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By Datadog
With over 426 million active users, comprised of consumers and merchants, Paypal processes approximately 25 billion transactions valued at around $1.53 trillion USD. Paypal is shaping the future of commerce for millions of customers globally, and to do that, they use Datadog to provide timely insights into their entire stack.
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By Datadog
OpenTelemetry (OTel) is an open source, vendor-neutral observability framework that supplies APIs, SDKs, and tools to instrument, generate, collect, and export telemetry data (metrics, logs, traces and soon profiles). It has a vibrant ecosystem of components, integrations and vendors. In this episode, Juliano Costa will discuss OpenTelemetry with Felix Geisendörfer, Senior Staff Engineer on the Continuous Profiling team, and Pablo Baeyens, Software Engineer on the OpenTelemetry team.
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By Datadog
At Datadog’s 2024 DASH conference, Anthropic President and Co-Founder, Daniela Amodei, announced the new Anthropic integration with Datadog’s LLM Observability. This new native integration offers joint customers robust monitoring capabilities and suite of evaluations that assess the quality and safety of LLM applications. Get real time insights into performance and usage, with full visibility into the end to end LLM trace. Enabling you to troubleshoot any issues, reduce downtime and get your Claude powered applications to market faster.
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By Datadog
Global financial services institutions monitor the health, security, and performance of their most business-critical systems with Datadog’s unified observability platform.
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By Datadog
Datadog provides real-time visibility and actionable insights into hybrid and multi-cloud environments, helping complex organizations streamline incident management, reduce costs, and maximize uptime in a single, unified platform.
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By Datadog
Whether you’re building a cloud architecture from scratch, documenting your current environment, or looking to optimize cloud cost, Cloudcraft allows you to visualize and communicate your architecture with ease.
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By Datadog
Datadog Container Monitoring gives you real-time, end-to-end visibility into the health, security, and resource usage of your containerized environments. In this demo, we’ll show you how Datadog measures container health alongside security posture and resource utilization, offering end-to-end monitoring and optimization for your container ecosystem.
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By Datadog
AI is hot, but it seems that many companies are haphazardly slapping AI onto their products. Often, these new AI-enabled tools seem more like a solution in search of a problem than a useful product. So how should we be incorporating AI to truly benefit our customers?
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By Datadog
As Docker adoption continues to rise, many organizations have turned to orchestration platforms like ECS and Kubernetes to manage large numbers of ephemeral containers. Thousands of companies use Datadog to monitor millions of containers, which enables us to identify trends in real-world orchestration usage. We're excited to share 8 key findings of our research.
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By Datadog
The elasticity and nearly infinite scalability of the cloud have transformed IT infrastructure. Modern infrastructure is now made up of constantly changing, often short-lived VMs or containers. This has elevated the need for new methods and new tools for monitoring. In this eBook, we outline an effective framework for monitoring modern infrastructure and applications, however large or dynamic they may be.
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By Datadog
Where does Docker adoption currently stand and how has it changed? With thousands of companies using Datadog to track their infrastructure, we can see software trends emerging in real time. We're excited to share what we can see about true Docker adoption.
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By Datadog
Build an effective framework for monitoring AWS infrastructure and applications, however large or dynamic they may be. The elasticity and nearly infinite scalability of the AWS cloud have transformed IT infrastructure. Modern infrastructure is now made up of constantly changing, often short-lived components. This has elevated the need for new methods and new tools for monitoring.
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By Datadog
Like a car, Elasticsearch was designed to allow you to get up and running quickly, without having to understand all of its inner workings. However, it's only a matter of time before you run into engine trouble here or there. This guide explains how to address five common Elasticsearch challenges.
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By Datadog
Monitoring Kubernetes requires you to rethink your monitoring strategies, especially if you are used to monitoring traditional hosts such as VMs or physical machines. This guide prepares you to effectively approach Kubernetes monitoring in light of its significant operational differences.
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Datadog is the essential monitoring platform for cloud applications. We bring together data from servers, containers, databases, and third-party services to make your stack entirely observable. These capabilities help DevOps teams avoid downtime, resolve performance issues, and ensure customers are getting the best user experience.
See it all in one place:
- See across systems, apps, and services: With turn-key integrations, Datadog seamlessly aggregates metrics and events across the full devops stack.
- Get full visibility into modern applications: Monitor, troubleshoot, and optimize application performance.
- Analyze and explore log data in context: Quickly search, filter, and analyze your logs for troubleshooting and open-ended exploration of your data.
- Build real-time interactive dashboards: More than summary dashboards, Datadog offers all high-resolution metrics and events for manipulation and graphing.
- Get alerted on critical issues: Datadog notifies you of performance problems, whether they affect a single host or a massive cluster.
Modern monitoring & analytics. See inside any stack, any app, at any scale, anywhere.