Welcome to the handbook on Anomaly Detection for Time Series Data! This series of blog posts aims to provide an in-depth look into the fundamentals of anomaly detection and root cause analysis. It will also address the challenges posed by the time-series characteristics of the data and demystify technical jargon by breaking it down into easily understandable language. This blog post (Chapter 1) is focused on.

Learn all about the most common challenges enterprises face when it comes to managing large-scale infrastructures and how Kentik’s network observability platform can help.

Imagine, if you will, having hundreds of devices that you need to monitor. All these devices generate data at sub-second intervals, and you need all that high fidelity data for historical analysis to feed machine learning models. Storing all that data can get really expensive, really fast. When that happens, you must decide what’s more important: keeping all your data or sacrificing insights and analysis. It may not be a big stretch of the imagination for many readers.

With our plans for InfluxDB 3.0 OSS laid out, both myself and the rest of the DevRel team have been actively searching for ecosystem platforms that would be logical integrations for the future of InfluxDB. One of these platforms is Quix! Quix is a comprehensive solution tailored for crafting, launching, and overseeing event streaming applications using Python. If you’re looking to sift through time series or event data in real-time for instant decision-making, Quix is your go-to.

Despite the rise of AI, the need for app developers isn’t going away. In fact, a 2023 ServiceNow-sponsored study by Pearson suggests approximately 95,000 new application developer roles will be added globally over the next five years. According to ServiceNow’s special report on the impact of AI on tech skills, based on the research, only about 20% of app developer tasks will be either automated or augmented by 2027.

The Slack messaging app is popular because it is easy to use, affordable, and highly customizable. With Slack, you can collaborate in teams and with colleagues in real-time, accessing files from anywhere. Slack is also widely used because it enables users to create and join channels. In addition, it integrates with multiple apps and services, working seamlessly with the tools you already use. In addition, Slack offers cost-effective pricing plans.

Organizations are moving to micro-services and container-based architectures because these modern environments enable speed, efficiency, availability, and the power to innovate and scale more quickly. However, when it comes to troubleshooting distributed cloud native applications, teams face a unique set of challenges due to the dynamic and decentralized nature of these systems.

Grafana is an open source visualization and monitoring solution for correlating and analyzing data from various sources. From time series graphs to heatmaps to 3D charts, it gives you lots of ways to untangle complex datasets. And while that’s incredibly powerful for observability, sometimes you’re looking for something fairly straightforward.

In recent months, we’ve talked a lot about how AppNeta by Broadcom offers active monitoring capabilities, and how they enable teams to rapidly troubleshoot issues across both internally managed networks and those managed by third parties, such as ISPs and cloud providers.

It's one of the most dreaded words among Kubernetes users. Regardless of your software engineering skill or seniority level, chances are you've seen it at least once. There are a quarter of a million articles on the subject, and countless developer hours have been spent troubleshooting and fixing it. We're talking, of course, about CrashLoopBackOff.