If you work as a CTO, then you already know that having robust monitoring and analytical tools for your technology stack is a prerequisite to getting your job done right. Many companies that started off using Datadog discovered that it can become prohibitively expensive and complex when they needed to scale. As such, there are a lot of people out there currently seeking out alternatives.
Any web-based business must have effective log monitoring in place to guarantee the efficient operation of its applications and systems. Tools for log monitoring are essential for error detection, performance analysis, and problem-solving. The top five log monitoring tools will be examined in this post, along with their features, prices, advantages, and disadvantages.
We’ve all been there. You’re working through some rather frustrating blockers during an incident only to discover that you don’t own the dependency at fault. Or, you’ve been pounding away at an issue when a fellow engineer reaches out and asks if your service is affected by some particularly gnarly database failure they’re seeing. But then what? Do you merge efforts and work in parallel or head for a coffee break while the issue gets attacked upstream?
GitLab is a DevSecOps platform that helps engineering teams automate software delivery. Using GitLab, teams can easily collaborate on projects and quickly deliver application code with robust CI/CD, security, and testing features. Datadog’s GitLab integration enables you to monitor your GitLab instances alongside the rest of your infrastructure by collecting GitLab metrics, logs, and service checks.
With the growing utilization of AI, modern business applications rely more and more on machine learning (ML) models. But the complexity of these models poses significant challenges to data scientists, engineers, and MLOps teams seeking to maintain and optimize performance.
In Elasticsearch 8.8, we’re introducing the reroute processor in technical preview that makes it possible to send documents, such as logs, to different data streams, according to flexible routing rules. When using Elastic Observability, this gives you more granular control over your data with regard to retention, permissions, and processing with all the potential benefits of the data stream naming scheme. While optimized for data streams, the reroute processor also works with classic indices.
Application Programming Interfaces (APIs) are a crucial building block in modern software development, allowing applications to communicate with each other and share data consistently. APIs are used to exchange data inside and between organizations, and the widespread adoption of microservices and asynchronous patterns boosted API adoption inside the application itself.