More and more employers are looking for people experienced in building and running Kubernetes-based systems, so it’s a great time to start learning how to take advantage of the new technology. Elasticsearch consists of multiple nodes working together, and Kubernetes can automate the process of creating these nodes and taking care of the infrastructure for us, so running ELK on Kubernetes can be a good options in many scenarios.
Breaking down larger, monolithic software, services, and applications into microservices has become a standard practice for developers. While this solves many issues, it also creates new ones. Architectures composed of microservices create their own unique challenges. In this article, we are going to break down some of the most common. More specifically, we are going to assess how observability-based solutions can overcome many of these obstacles.
This article is part 2 of a four-part series of articles about Elasticsearch performance monitoring. Part 1 explains what Elasticsearch is and how it works, while in this part, we’re going to look at Elasticsearch’s capabilities and potential use cases, and how to check its status. We’ll identify key metrics that you need to monitor to maintain the health and performance of your Elasticsearch cluster.
As we’re doing our best to make monitoring easy, we’ve wanted to make more content that would really show and not just tell you how easy it is to set up monitoring with AppSignal. We’ve been collaborating with Leigh Hallday on making this video for you that will show you everything you need to know about the setup process. We’ll be posting more videos like this on our YouTube channel, so you should subscribe to it if you’d like to get notifications about future videos.
When providing services to your customers you need to keep an eye on everything that could impact your success with that – from low-level performance metrics to high-level business key performance indicators. From server-side logs to stack traces giving you full visibility into business and software processes that underpin your product. That’s where cloud monitoring tools and services come into play.
To enhance and automate your vulnerability analysis, we’re excited to launch the Datadog Vulnerability Analysis GitHub Action. The action enables easy integration between your application, Datadog Continuous Profiler, and Snyk’s vulnerability database to provide actionable security heuristics. The action can be installed directly from the GitHub Marketplace, and does not require you to manage any additional scripts or infrastructure.
Integrations bring your favorite tools together, making them more useful, easier to incorporate into your existing operations, saves time, and prevents confusion. That’s why Uptrends continues to add more Integrations to your alerting options.
Inspecting complicated network issues shouldn’t require you to switch between multiple tabs and network records. Solving these issues often boils down to finding the IP addresses of a network entity. Be it a desktop, server, port, or some other entity, its IP address gives you much-needed insight into details like its asset tag, interface specifics, user, and device type. This information helps you get to the bottom of network issues, aiding in effective troubleshooting.
Several factors in recent years have increased endpoint vulnerability — from organizations’ need to make access to data more fluid, to threats targeting mobile device access and networks, to the growing work-from-home and work-on-the-go trends. Endpoints connected to a network — including remote devices, IoT devices, workstations, tablets, laptops and servers — create attack paths for security threats.
