How would you compare the Windows and macOS operating systems? In what ways are they similar? Why do they each take different approaches to solving the same problem? For the last 19 years I've developed security software for Windows. Recently, I’ve started implementing similar features on macOS. Since then, people have asked me questions like this. The more experience I gained on these two operating systems, the more I realized they’re very different.

We are pleased to announce the availability of the Elastic OpenTelemetry integration — available on Elastic Cloud, or when you download Elastic APM. This integration continues our to openness by embracing open standards support for the evolving OpenTelemetry standard for observability

While we know the many benefits of going serverless - reduced costs via pay-per-use pricing models, less operational burden/overhead, instant scalability, increased automation - the challenges are often not addressed as comprehensively. The understandable concerns over migrating can stop any architectural decisions and actions being made for fear of getting it wrong and not having the right resources.

Enterprise monitoring tools have traditionally paid attention to the performance of monolithic applications hosted on physical and virtual infrastructure resources. The adoption of cloud native and microservices architectures has brought greater focus to end-user experiences delivered by web applications across different global locations. The bar for a great digital customer experience has never been higher.

Throughout the history of software development, one statement has remained true: no application is perfect. Due to that fact, development organizations must work with all resources at their disposal to limit the impact that application problems have on the end-user. Server log files represent an important resource that should be referred to during the process for troubleshooting any application issue.

Do you have a big data center? Do you have terabytes of confidential data stored in that data center? Are you worried that your data might be exposed to malicious attacks? One of the most prominent security features of storage solutions is encryption at rest. This blog will explain this in more detail and how it is implemented in Charmed Ceph, Canonical’s software-defined storage solution.

This blog series is part of the joint collaboration between Canonical and Manceps. Visit our AI consulting and delivery services page to know more. Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is a part of the Kubeflow project that aims to reduce the complexity and time involved with training and deploying machine learning models at scale. For more on Kubeflow, read our Kubernetes for data science: meet Kubeflow post.

The first thing we tell Graylog users is, “Monitor your disk space.” The core set of metrics discussed below should always be in acceptable parameters and never grow over extended periods without going back to normal levels. This is why it is critical to monitor metrics that come directly from the hosts running your Graylog infrastructure.

Information security (infosec) is a broad field. Its practitioners behave more like artists than engineers. After all, the mandate for security is not “do X”, but instead “ensure no one can do X, Y, Z, ɑ, β, ɣ, etc.”. The array of possibilities leading to infosec failure are vast. It’s like trying to prove a negative, thus making the task near impossible. On one hand we have an impossible task, on the other we have the affordance of time.

This article was written by Gregory Scafarto, Data Scientist intern at Supralog, in collaboration with InfluxData’s DevRel Anais Dotis-Georgiou. At InfluxData, we pride ourselves on our awesome InfluxDB Community. We’re grateful for all of your contributions and feedback. Whether it’s Telegraf plugins, community templates, awesome InfluxDB projects, or Third Party Flux Packages, your contributions continue to both impress and humble us.