Operations | Monitoring | ITSM | DevOps | Cloud

Cloud are on the rise! User concerns about data storage security and their need for quick access to databases are driving the development of cloud technologies. At the moment, the most progressive and convenient solution is hybrid cloud storage. The significant current popularity and predicted growth in demand for hybrid cloud technologies in the near future are not just speculation. They are evidenced by research.

A look at best practices, no-code and low-code platforms you can use, common visualization types, criteria for good data visualization and more. Organizations regularly generate an overabundance of data that is essential for decision-making. Data visualizations play an important role in helping people understand complex data and observe patterns and trends over a period of time.

Modern computing environments and distributed workforces have produced new challenges to traditional information security approaches. Many traditional threat detection and response strategies rely on homogeneous environments, system baselines, and consistent control implementations. These strategies have been built on traditional environment assumptions that may no longer be true in your environment with the evolution of cloud computing, remote work, and modern culture.

Elastic has an entirely new Heartbeat/Synthetics workflow superior to the current workflow. If you’re a current user of the Elastic Uptime app, read on to learn about the improved workflow you can use today and should eventually migrate toward.

OpenTelemetry consists of several main components. But to understand the architecture, we will start by understanding some of the key design principles behind the design and architecture of OpenTelemetry. But before that, let us have a brief overview of OpenTelemetry.

In an earlier blog post we talked about how to stream data from the Mastodon timeline into an Apache Kafka® cluster. If you missed it, read it to learn how to connect to Mastodon and stream data into an Apache Kafka topic. This article assumes that you already have an Apache Kafka environment running with data in a topic that is called Mastodon.

Unmanageable incidents are what nightmares are made for – as far as ITOps managers and their teams are concerned. Sometimes, risks become issues. Other times, incidents turn into problems. Any of these could lead to disastrous consequences, such as security breaches, unexpected data risks, and unplanned application downtimes, which directly impact the organization.

Developer environments can streamline testing, and can encourage experimentation and creativity from engineers and non-engineers alike. In this article, we’ll take a look at the pros and cons of developer environments, and dive into best practices for those who adopt them.

In this series, we’ve been exploring the different layers of business value you can gain from deploying software more frequently. We’ve already looked at the hard costs you can save, and the valuable developer time you can recoup. But that’s not the end of the story. Not by far. Picture an iceberg. The top, the visible part, is those hard costs. Just beneath the surface is that time that can be gained by redeploying wasted time to projects that matter.

In my last blog I took a look at some of what I see as the most obvious signs that your MSP business might have outgrown its RMM. These included: In this blog, I’m going to turn my attention to looking at some of the less obvious signs to reconsider your RMM.