Operations | Monitoring | ITSM | DevOps | Cloud

As the team responsible for building dormakaba’s first cloud-access control solution, Exivo, the Cloud Development team at dormakaba AS EMEA needed a logging solution that with scalable logging throughout their global environment, handle a huge amount of throughput, be piped through an API, and remain highly secure so it could be implemented on the doors and entry systems the company produces. Logz.io was the perfect fit for these requirements.

Kinesis is a managed, high-performance and large-capacity service for real time processing of (live) streaming data. Prominent users include Netflix, Comcast and Major League Baseball. Its design to let it grab data from multiple sources at the same time and to scale processing within EC2 instances.

In a previous article, we examined service meshes in detail. Briefly, a service mesh takes care of network functionality for the applications running on your platform. As Kubernetes has matured as a technology, service meshes have become a hot topic, with various products being developed to solve the challenges associated with areas like traffic management, security, and observability. This article will compare three service meshes.

Microservices constantly change in containerized environs, making pod or node identification and their logging more of a challenge. Autodiscover simplifies monitoring movements in these sorts of environments—places like Kubernetes and Docker. Autodiscover allows you to track pods and adapt settings as changes happen in your environment.

Snyk is a developer-centric company whose raison d’être is to identify and patch vulnerabilities in open source security software. With about 50 engineers, Snyk VP Engineering Anton Drukh wants to maintain flexibility in how the team operates. The best way to ensure that is to give them as much insight into their own work as possible, and hence options. They also look at the state of open source security across the industry.

New technology presents itself as a difference-maker. Every new application has the power to streamline routine tasks or faulty systems. But a dose of reality can damper the hype, as the Iowa caucuses app did this week. Instead of hope and hype, they inspire doubt and maybe scorn. With democracy, there is also a fear that we don’t control our own votes—hackers or foreign powers might be trying to steal the results for their own reasons.

You might be on the move. You might be breaking into the field. You might be trying to level up with your next gig. You might be ready for a manager’s role. Regardless of the reason, you are wondering what you need to re-study for your job interviews and “homework” assignments. Even with years of experience, every new gig expects you to answer different kinds of DevOps interview questions.

Let’s face it—distributed streaming is an exciting technology that can be leveraged in many ways. Use cases include messaging, log aggregation, distributed tracing, and event sourcing, among others. Distributed streaming can result in significant benefits for companies that choose to use it, but, when not implemented correctly, it can initiate a frustrating technical debt cycle. How do you know if you’re properly implementing Kafka in your environment?

2020 is here and it looks like it’ll be a truly exciting and impactful year for the DevOps community. As you know, the landscape is changing rapidly, and as a result, new technologies and methodologies are emerging to solve challenges you’re experiencing on the job. Observability is one such concept–and achieving it is a huge challenge for software engineers across the globe.

Redis is an extremely fast NoSQL data store. While it is used mainly as a cache, it can be applied to uses as diverse as graph representation and search. Client libraries are available in all of the major programming languages, and it is provided as a managed service by all of the top cloud service providers. For the past three years, Redis has been named the most loved database by the Stack Overflow Developer Survey.