Jon Fautley

if you're interested on how at LANDBAY we've combined the use of Terraform, Flux, EKS and the rest of the AWS platform, then this can hopefully serve as a blueprint... https://lnkd.in/eW-VWqCn

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Missed one aspect of writing the TLA+ spec yesterday. How to gain confidence it is correct. https://lnkd.in/dQn2VUUq

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🚀 Deploying #Konnect just got easier 🚀 Kong Inc. have just released a sleek new terraform provider to deploy Kong Konnect with ease. 🔗 Check out the terraform provider just released in BETA: https://lnkd.in/exkTDYy7 This is a significant step towards enhancing the efficiency and reliability of API management workflows. Kudos to the Kong Inc. team for this incredible addition! 👏 Let’s harness the power of automation and take our API deployments to the next level. Happy deploying! 🚀 Great blog post by Michael Heap at Kong that goes into more detail about the new provider 👇 #kong #kongkonnect #terraform #devops #automation #iac #apideployment #quadcorps #weareintegration

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Kubernetes Tips: We all do pod limits in our K8 setups , how many of us do pid limits? To know why its important read https://lnkd.in/dxURNjmY . Thanks Xing Du , your coffee is brewing :)

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New to Kubernetes? Meet the game-changing duo: Portainer + Sidero Talos! In our latest blog, we explore how combining Portainer’s intuitive management interface with Sidero Talos’s secure, bare-metal Kubernetes OS can simplify Kubernetes for emerging platform engineers. From reducing complexity to enhancing security, this integration makes cluster management and operations a breeze. 🔗 Read the blog: https://bit.ly/4f5ZZoK Sidero Labs, Inc. #Portainer #Kubernetes #PlatformEngineering #SideroTalos #DevOps #CloudComputing

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Amped for #AWSreInvent? Same. We’ll be there in force – learning, mingling and sharing ideas. We’ll also be presenting some of the breakthrough work we’re doing around how our data and cloud environments help us to innovate with #AI . Are you going to Vegas? Drop a comment below. https://bit.ly/3YYRSU4

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Following on from the fundamentals course there is GitOps at Scale where I learned about deploying multiple applications to multiple clusters using a variety of patterns, promoting releases, and common operations including sync phases/hooks, sync waves and notifications all with ArgoCD. Codefresh #ArgoCD

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For those of you new to Terraform, check out this video from my colleague Sarah Lean. It’s a good place to start for an aspiring Azure Terraformer!!! 😊 https://lnkd.in/eTaZF738

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tl;dr Switching EC2 and/or RDS to Graviton instances can give a ~20% cost saving usually with the same or even better performance.

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Importing Existing Cloud Resources into Terraform https://lnkd.in/e_yPu-ZN #TerraformMigration #CloudInfrastructureAsCode #TerraformAutomation #CloudResourceImport #InfrastructureMigration #TerraformOnboarding #CloudToTerraform #AutomateWithTerraform #CloudResourceManagement #TerraformIntegration

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Terraform has long been the industry standard tool for implementing Infrastructure as Code (IaC), but could this be about to change with the emergence of AWS CDK? With two years of experience in Terraform and having recently completed an upskilling project on CDK, Annabel Canham compares the experience of coding with Terraform and AWS CDK and reflects on the reasons why you might want to opt for one over the other. https://buff.ly/3XZfRC7 #AWS #Terraform #InfrastructureAsCode

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🕵️‍♀️ Kubernetes Secrets got you puzzled? Sam Gabrail, Platform Engineer and trainer, has your back. In his latest video and blog, Sam demystifies Kubernetes Secrets, busts common myths, and shows you how to secure them effortlessly with Akeyless Security. Learn: ✔️What Kubernetes Secrets are and why you need them. ✔️Types of Kubernetes Secrets and their uses. ✔️Common misconceptions debunked. ✔️Hands-on demo with Akeyless. Check the blog and video for clear, actionable insights and take control of your Kubernetes Secrets. Read here to get started! https://hubs.li/Q02GWyGl0 #DevOpsTool #SecretsManagment #PlatformTeams

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🕵️ Unlock the secrets of troubleshooting containerized apps 👀 Attend our k8s application failure workshop! In this hands-on workshop, we’ll dive into real-world scenarios and learn essential techniques to: ✅ Debug unexplained OOMKills ✅ Resolve mismatched Kubernetes configurations ✅ Overcome connection throttling issues ✅ Unblock stubborn threads Don’t miss this chance to elevate your troubleshooting game! Sign up now: https://ln-s.io/4eyBGPb cc: Prequel.dev #DevOps #Kubernetes #k8s #Observability #SRE #CloudInfrastructure

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Having OTel boilerplate fatigue? Give this Python decorator a try :) - https://lnkd.in/ef_6jXrg #opentelemetry #observability #python

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So this is interesting... I'm not a fan of AI - I personally think AIs are far too expensive (runtime/training costs) when compared to the actual benefit they provide. But code reviews... This becomes interesting. Because although there are "build-time pluggable" automation options (check-style, find-bugs, various linters), that can apply defined rules, these can't read or understand documentation or review context. But LLMs *_can_* understand the written text in comments and review exchanges! And perhaps more importantly, LLMs are tools - so they won't get irritable, have mood swings, or otherwise behave inconsistently like a human reviewer (me, for example) would. So they can (and do!) offer guidance on fixing review issues that I might be too irritable, or otherwise disinclined to offering. So, yes, it is still an expensive tool (power consumption, carbon footprint, training resource investment etc) - but it does something that adds value for once. Is this enough value add to balance the expense though? Not sure about that yet! https://lnkd.in/excctgva

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Tiered storage for Kafka Kafka cluster storage is typically scaled by adding more broker nodes to the cluster. But this also adds needless memory and CPUs to the cluster, making overall storage cost less efficient compared to storing the older data in external storage. A larger cluster with more nodes also adds to the deployment complexity and increases operational costs because of the tight coupling of storage and processing. So, it brings several issues related to scalability, efficiency, and operations. In the tiered storage approach, Kafka cluster is configured with two tiers of storage - local and remote. The local tier is the same as the current Kafka that uses the local disks on the Kafka brokers to store the log segments. The new remote tier uses systems, such as HDFS or S3 to store the completed log segments. Two separate retention periods are defined corresponding to each of the tiers. With remote tier enabled, the retention period for the local tier can be significantly reduced from days to few hours. The retention period for remote tier can be much longer, days, or even months. When a log segment is rolled on the local tier, it is copied to the remote tier along with the corresponding indexes. Latency sensitive applications perform tail reads and are served from local tier leveraging the existing Kafka mechanism of efficiently using page cache to serve the data. Backfill and other applications recovering from a failure that needs data older than what is in the local tier are served from the remote tier. #kafka #storage #cost https://lnkd.in/ehu2Fw2v

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Portainer 2.21.0 LTS is an essential update for Kubernetes users. Along with support for new Kubernetes versions we've extended the object types you can manage with Portainer, including Service Accounts, Roles and Role Bindings, and Cluster Roles and Cluster Role Bindings. You can find these objects under More Resources when managing a Kubernetes environment. To learn more about our Kubernetes updates in 2.21.0 LTS have a look at our blog post: https://bit.ly/4g6n3UZ

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It was truly an honour to facilitate a talk with the CTO Tom Wilkie and Co-Founder Anthony Woods of Grafana Labs, exploring the evolving landscape of Observability tools through the perspective of Site Reliability Engineering (SRE). Observability, encompassing the holistic view of systems with its three pillars traces, logs, and metrics emerged as a central theme, emphasising the significance of considering all aspects. The adoption towards SLO/SLIs has gained momentum in SRE efforts across the industry, highlighting the importance of defining the right SLO and SLI for services and applications to effectively support your systems. The discussion underscored the critical role of selecting the right ruleset in navigating this complex terrain. Additionally, it was fascinating to see how Grafana is contributing to the ecosystem amidst the sprawl of observability tools. Their efforts in enhancing the accessibility and usability of these tools are undoubtedly shaping the way organisations manage and monitor the systems

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