Colt McNealy’s Post

Modern Approaches to Continuous Integration https://lnkd.in/e5YtxZNz Solomon Hykes (@solomonstre, Co-Founder @Dagger_io) talks about the evolution of the container industry, fixing broken CI/CD systems, and modern DevOps.

Is DevOps losing its shine? Cloud platform engineering is the latest trend, but it can be time consuming and seem very tedious to maintain. Enter platform engineering – a modern approach to building and maintaining a platform that frees up developers from infrastructure management. Curious about the future? Hear Kumulus CTO, Robert Starmer, share his thoughts on the latest episode of Kumulus on Cloud. #DevOps #PlatformEngineering #Cloud https://hubs.la/Q01Ysddq0

Is DevOps losing its shine? Cloud platform engineering is the latest trend, but it can be time consuming and seem very tedious to maintain. Enter platform engineering – a modern approach to building and maintaining a platform that frees up developers from infrastructure management. Curious about the future? Hear Kumulus CTO, Robert Starmer, share his thoughts on the latest episode of Kumulus on Cloud. #DevOps #PlatformEngineering #Cloud https://hubs.la/Q01Ysc0Q0

Kubernetes is a powerful container orchestration platform that has become increasingly popular in recent years. However Monitoring a Kubernetes cluster can be a daunting task. With so many moving parts, it can be difficult to know where to start. But it's essential to get monitoring right, or you could be setting yourself up for failure. 🧨 One of the biggest challenges of Kubernetes monitoring is the dynamic nature of the platform. Pods are constantly being created, updated, and deleted. This means that your monitoring solution needs to be able to keep up with the changes. 🌐Another challenge is the distributed nature of Kubernetes. Metrics are collected from different parts of the cluster, and it can be difficult to get a unified view of the health of the system. 🎯But there are solutions to these challenges. ✅ Prometheus is a popular open-source monitoring system that is designed to be scalable, flexible, and easy to use. It can collect metrics from all parts of the Kubernetes cluster, and it provides a unified view of the health of the system. ✅ Grafana is a popular open-source dashboarding solution that can be used to visualize Prometheus metrics.  It allows you to create custom dashboards that track the health of your Kubernetes cluster. 🤝Together, Prometheus and Grafana can provide you with a comprehensive monitoring solution for your Kubernetes cluster. With the right monitoring in place, you can be confident that your cluster is healthy and running smoothly. Let's have a quick look at some additional tips for Kubernetes monitoring: ✅ Use a service discovery tool to automatically discover your pods. ✅ Use a centralized logging solution to collect logs from all parts of your cluster. ✅ Set up alerts so that you are notified of any problems. ✅ Regularly review your monitoring data to identify trends and potential problems. With these tips you can ensure that your Kubernetes cluster is properly monitored and that you are alerted to any problems as soon as they occur. Original post from Chandresh Desai #devops  #kubernetes  #cloudcomputing  #devopstools  #softwareengineering  #cloud

We cordially invite you to partake in our no-cost webinar about Stream Processing, coming to you courtesy of #Capgemini and #Confluent. Key on your calendar the date: 17th of April, from 1 to 2PM. The underpinning role of Stream processing in the architecture stack dedicated to data streaming is indubitable. Developers can wield it as a tool to filter, merge, pool and transform their data streams at the blink of an eye. The result? Powering applications in real time and enriching streaming data conduits becomes a breeze. While several stream processing frameworks exist, Apache Flink has made its mark as the go-to standard, enjoying this position due to its top-notch performance and plethora of useful features. However, using Flink on a self-management model (much like some other open-source utilities such as Kafka) can be onerous, given its intricate operational design, sharp learning gradient, and costly support resources when kept in-house. This complimentary online seminar will offer a comprehensive delve into Confluent Cloud for Apache Flink®, presented as the only cloud-native, serverless Flink service in the industry made for processing data in-flight. It has the prowess to generate premium, reusable streams, that can be transmitted anywhere in real-time. An insightful technical demonstration will also engage you, showcasing the broad spectrum of capabilities Flink possesses on the Confluent Cloud. Pledge your free participant's spot now, and equip yourself on how to: Harness Flink to filter, fuse, and enrich your data streams, leveraging on the default standard for stream processing Unleash high-output and efficient stream processing at any given scale, minus the hurdles of managing infrastructure Experience the seamless blend of Kafka and Flink as a holistic platform, replete with integrated monitoring, fortified security, and governance. Reserve your spot now at: https://lnkd.in/ertUBhw8.

We cordially invite you to partake in our no-cost webinar about Stream Processing, coming to you courtesy of #Capgemini and #Confluent. Key on your calendar the date: 17th of April, from 1 to 2PM. The underpinning role of Stream processing in the architecture stack dedicated to data streaming is indubitable. Developers can wield it as a tool to filter, merge, pool and transform their data streams at the blink of an eye. The result? Powering applications in real time and enriching streaming data conduits becomes a breeze. While several stream processing frameworks exist, Apache Flink has made its mark as the go-to standard, enjoying this position due to its top-notch performance and plethora of useful features. However, using Flink on a self-management model (much like some other open-source utilities such as Kafka) can be onerous, given its intricate operational design, sharp learning gradient, and costly support resources when kept in-house. This complimentary online seminar will offer a comprehensive delve into Confluent Cloud for Apache Flink®, presented as the only cloud-native, serverless Flink service in the industry made for processing data in-flight. It has the prowess to generate premium, reusable streams, that can be transmitted anywhere in real-time. An insightful technical demonstration will also engage you, showcasing the broad spectrum of capabilities Flink possesses on the Confluent Cloud. Pledge your free participant's spot now, and equip yourself on how to: Harness Flink to filter, fuse, and enrich your data streams, leveraging on the default standard for stream processing Unleash high-output and efficient stream processing at any given scale, minus the hurdles of managing infrastructure Experience the seamless blend of Kafka and Flink as a holistic platform, replete with integrated monitoring, fortified security, and governance. Reserve your spot now at: https://lnkd.in/e3DJ3R3p.

We cordially invite you to partake in our no-cost webinar about Stream Processing, coming to you courtesy of #Capgemini and #Confluent. Key on your calendar the date: 17th of April, from 1 to 2PM. The underpinning role of Stream processing in the architecture stack dedicated to data streaming is indubitable. Developers can wield it as a tool to filter, merge, pool and transform their data streams at the blink of an eye. The result? Powering applications in real time and enriching streaming data conduits becomes a breeze. While several stream processing frameworks exist, Apache Flink has made its mark as the go-to standard, enjoying this position due to its top-notch performance and plethora of useful features. However, using Flink on a self-management model (much like some other open-source utilities such as Kafka) can be onerous, given its intricate operational design, sharp learning gradient, and costly support resources when kept in-house. This complimentary online seminar will offer a comprehensive delve into Confluent Cloud for Apache Flink®, presented as the only cloud-native, serverless Flink service in the industry made for processing data in-flight. It has the prowess to generate premium, reusable streams, that can be transmitted anywhere in real-time. An insightful technical demonstration will also engage you, showcasing the broad spectrum of capabilities Flink possesses on the Confluent Cloud. Pledge your free participant's spot now, and equip yourself on how to: Harness Flink to filter, fuse, and enrich your data streams, leveraging on the default standard for stream processing Unleash high-output and efficient stream processing at any given scale, minus the hurdles of managing infrastructure Experience the seamless blend of Kafka and Flink as a holistic platform, replete with integrated monitoring, fortified security, and governance. Reserve your spot now at: https://lnkd.in/d7NPsBc5.

Kubernetes is a powerful container orchestration platform that has become increasingly popular in recent years. However Monitoring a Kubernetes cluster can be a daunting task. With so many moving parts, it can be difficult to know where to start. But it's essential to get monitoring right, or you could be setting yourself up for failure. 🧨One of the biggest challenges of Kubernetes monitoring is the dynamic nature of the platform. Pods are constantly being created, updated, and deleted. This means that your monitoring solution needs to be able to keep up with the changes. 🌐Another challenge is the distributed nature of Kubernetes. Metrics are collected from different parts of the cluster, and it can be difficult to get a unified view of the health of the system. 🎯But there are solutions to these challenges. ✅Prometheus is a popular open-source monitoring system that is designed to be scalable, flexible, and easy to use. It can collect metrics from all parts of the Kubernetes cluster, and it provides a unified view of the health of the system. ✅Grafana is a popular open-source dashboarding solution that can be used to visualize Prometheus metrics.  It allows you to create custom dashboards that track the health of your Kubernetes cluster. 🤝Together, Prometheus and Grafana can provide you with a comprehensive monitoring solution for your Kubernetes cluster. With the right monitoring in place, you can be confident that your cluster is healthy and running smoothly. Let's have a quick look at some additional tips for Kubernetes monitoring: ✅Use a service discovery tool to automatically discover your pods. ✅Use a centralized logging solution to collect logs from all parts of your cluster. ✅Set up alerts so that you are notified of any problems. ✅Regularly review your monitoring data to identify trends and potential problems. With these tips you can ensure that your Kubernetes cluster is properly monitored and that you are alerted to any problems as soon as they occur. ♻️Repost if you find this valuable! #devops #kubernetes #cloudcomputing #devopstools #softwareengineering #cloud

The latest update for #Rancher includes "Deploy s3gw in Digital Ocean" and "Challenges and Solutions with CloudNative Persistent Storage". #devops #cloud #Kubernetes https://lnkd.in/d6Kik_K

Check out the latest #Nuanix University video to learn how to effortlessly deploy a Kubernetes cluster in one click on the Nutanix Cloud Platform.