dapr

Dapr: Distributed Application Runtime

Dapr – a toolbox for distributed systems The growing complexity of distributed, containerized systems presents many developers with new challenges. This creates new interfaces within an application, which also require new approaches for the integration. Further problems arise not only technically but also organizationally for projects and their operation. Essentially, this raises some questions. Who must provide the necessary systems for the integration layer within a distributed application? Who manages this layer? Who is responsible Weiterlesen…

How I Prepared for and Passed the CKA Exam (v1.21)

Introduction In February 2021, I started working at Liquid Reply and consequently with Kubernetes. Kubernetes’ concepts, ideas, and workflows were entirely new to me. My previous jobs in the last decade were all in the field of classic Linux administration. I did everything from provisioning to decommission computing, storage, and networking hardware in data center environments. I managed Linux workstations, maintained a custom Linux kernel as well as custom packages. That is the reason why Weiterlesen…

HowTo: Send your Alerts to Microsoft Teams

Gathering metrics and logs from your applications is usually not enough. You want to receive alerts if something is suspicious and then investigate in a dashboard solution like Grafana or Kibana. At Liquid Reply, we had to find a solution to send our alerts from the Alertmanager to Microsoft Teams. Our initial setup consisted of Prometheus, which is gathering all the metrics, and Alertmanager that was attached to Prometheus. This Alertmanager was sending notifications to Weiterlesen…

FinOps + Policy-as-Code

FinOps brings financial accountability to the variable spend model of cloud, enabling distributed teams to make business trade-offs between speed, cost, and quality. FinOps definition at Cloud FinOps by J.R. Storment; Mike Fuller tl;dr: Writing FinOps-guided governance policies will help with your Cloud Cost Optimization. In this post, we spend some time trying to use simple words in order to explain the concept of FinOps, as well as Policy-as-Code. What is FinOps The term FinOps Weiterlesen…

Intro to Distributed Systems and traceability using Jaeger – Pt.2

To me, Traceability is basically logging but in a better and more structured context. In the first part of this series, we discussed the history of distributed systems and microservices, giving Amazon website as an example of how the microservices would look like and inter-communication between them all. Moving forward, what to use to debug a service request that goes through many microservices and you want to correlate all of the events and transactions that Weiterlesen…

Intro to Distributed Systems and traceability using Jaeger – Pt.1

“If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it”  Albert Einstein once said that. Now imagine that this planet in this scenario is your system which you’re responsible for operating and maintaining the availability and durability of the system. Where probably a system contains several functions are communication to each other and you can’t possibly identify what went wrong or where. Imagine you just received an issue that a service Weiterlesen…

An introduction to Loki

Many enterprise customers are using ELK to store the logs from their Kubernetes clusters. Others are using solutions the cloud provider offers like Stackdriver or Cloudwatch. While ELK is difficult to configure and to operate, managed solutions are quite easy to use but they lead into a Vendor Lock-In. Both solution models are quite expensive if you want to store a big number of logs and if you have more than a few Kubernetes clusters. Weiterlesen…

HowTo: Use the Logging-Operator

Many people are leveraging fluentd, fluent-bit or the ELK-stack in combination with filebeat to collect their logs from Kubernetes clusters. These options are often complicated to configure or not flexible enough to use for different teams. We were looking for an easy way to collect our logs. Besides that, the customer wanted an option to do this, too. In the end we decided to use the logging-operator by banzaicloud. It is utilizing a DaemonSet of Weiterlesen…

Monitor your Multi-Cluster-Environments

While countless companies are starting to use Kubernetes to offer their services and applications, many are experiencing the classic problems of “Day-2 operations”: The systems are often not optimized, maintenance aspects are missing, or observability concepts are not sufficiently or incorrectly implemented. A common problem is that existing monitoring and logging solutions cannot be used, because they do not fit the requirements of distributed systems and Multi-Cluster-Environments. Problems of monitoring distributed systems But why is Weiterlesen…

Scale out your Raspberry-Pi Kubernetes cluster to the cloud

Using Gardener Machine-Controller-Manager and Tailscale to extend a local Raspberry-Pi K3s cluster with cloud instances. tl;dr watch the Video from Christoph presenting this solution at the Gardener Meetup Intro Like a lot of Kubernetes enthusiasts, I grabbed a couple of Raspberry Pis, followed the instructions of Alex Ellis, and created a K3s cluster. I don’t want to repeat this instruction here, Alex did a great job explaining how to prepare the Machines and a K3s Weiterlesen…