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Australia & New Zealand cloud teams, you won't want to miss this! Are your developers struggling to use Terraform or OpenTofu effectively? Is your platform team stuck on the operational treadmill, spending too much time supporting individual developers' infrastructure requests?  Are you dealing with the risks and costs inherent in infrastructure misconfiguration, especially when trying to drive adoption? Join Travis McPeak and Chamara Somaratne in 2 weeks as they cover how to adopt infrastructure as code at scale without wasting time and energy stuck in ops mode. Register today 👉 https://lnkd.in/etjt8FGT #IaC #cloud #DevOps #Terraform #security

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Disaster recocery and backup are boring but critical.

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AWS Lambda recursive loops can be a bottleneck. Our latest blog provides practical steps to understand, prevent, and resolve these issues effectively. Explore insights and best practices for seamless AWS environment optimization. 🔍 Dive deeper: https://lnkd.in/g6YirpXH

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💪 Claude 3.5 Sonnet runs on GitHub Copilot via Amazon Bedrock!!!! 💪 🎙 💥Mic drop🎙 💥 https://lnkd.in/g4_UhY-c https://lnkd.in/gcnwy2QQ #aws #genai #bedrock #anthripic #GitHub #Copilot

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Updated guide —> EKS Best Practices for Load Balancing - https://lnkd.in/guv8Q9uK #aws #eks #loadbalancing #eksbestpractices #cloudcomputing

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Kubernetes are offering rich set of APIs to help administrators manage their clusters as well as developers creating their applications. Those APIs are widely used in defining the YAML templates for: • deploying resources and applications • managing cluster policies • setup storage/volumes • networking • configuring flow control • manage scheduling. You can easily get the set of APIs by running the command: kubectl api-versions. Below are the list of APIs and their functionality: 1.'https://lnkd.in/ejBg_zvu': Manages admission webhooks, which are used to modify or validate requests to the Kubernetes API. 2. apiextensions.k8s.io/v1: Manages Custom Resource Definitions (CRDs), which allow users to create custom resources that extend Kubernetes with new APIs. 3. apiregistration.k8s.io/v1: Manages the registration of API services, allowing users to extend the Kubernetes API with additional services. 4. apps/v1: Manages stateful and stateless applications. 5. authentication.k8s.io/v1: Handles authentication resources and methods. 6. authorization.k8s.io/v1: Manages access control through role-based access control (RBAC) and other authorization mechanisms. 7. autoscaling/v1: Manages auto-scaling of workloads. 8. autoscaling/v2: An enhanced version of autoscaling/v1 with more advanced metrics and scaling policies. 9. batch/v1: Manages batch jobs and cron jobs. 10. certificates.k8s.io/v1: Manages certificate signing requests (CSRs) within the cluster. 11. coordination.k8s.io/v1: Manages leases, which are often used for leader election in high-availability components. 12. discovery.k8s.io/v1: Manages EndpointSlices, which provide a scalable way to represent network endpoints for a Kubernetes service. 13. events.k8s.io/v1: Manages events, which are records of actions that have occurred within the cluster. 14. 'https://lnkd.in/edFiiYnb': Manages API request flow control, which prioritizes API requests to ensure that critical system operations are handled efficiently. 15. https://lnkd.in/eqV-u3vP: A beta version of the https://lnkd.in/edFiiYnb API, providing similar functionality with possible experimental features. 16. networking.k8s.io/v1: Manages networking resources, including services and ingress. 17. node.k8s.io/v1: Manages resources related to nodes in the Kubernetes cluster. 18. policy/v1: Manages policies related to security and pod behaviour. 19. https://lnkd.in/eTdjVy4R: Manages role-based access control (RBAC) resources. 20. scheduling.k8s.io/v1: Manages scheduling policies and resources. 21. storage.k8s.io/v1: Manages storage-related resources. 22. v1: This is the core API group, managing fundamental resources in Kubernetes.

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reviewing Kafka next will be Kafka = AWS MSK Cluster then Lambda + MSK

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Seeing what is running in your cloud architecture improves comprehension, speeds up onboarding, assists with cost minimisation and troubleshooting. If you are building on #AWS, #Azure or #GCP check this out: https://lnkd.in/gyEGkS4U

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We did AWS Cost Optimisation for one of our clients and were able to reduce the cost from a whopping $85K/month to $29K/month 💰 📉 You can read the full article here - https://lnkd.in/gT9eKJXw Summary of the key steps taken, ✏️ Get familiarised with the AWS Cost Explorer and use filters to understand & start optimizing the service that is costing more 🎭 Multi-AZ setup is important, but not for all the envs. Cross AZ communication even within the same region will incur cost. So design the Infrastructure keeping the Data Transfer cost into consideration 🧠 Have the Architecture knowledge to know the Resilient and Sensitive components. Use Spot Instance & Savings plan effectively to reduce 30 - 40% of the cost 💪 While AWS-managed services come with easy maintenance, you will pay a much higher cost compared vs running it in a VM. Especially, AWS MSK Vs Kafka, AWS Elasticache Vs Redis 🙅‍♂️ Stop the machines that are not in use! It is very simple, but not an easy one. Understand System design, Leverage Cloudwatch metrics, and Collaborate with the dev team to understand if the VM is put to proper use or not. Still, there is lot of scope for further optimizations 👀 Let me know what methods/techniques you followed to optimize the AWS Cloud Costs 😇 #aws #cost-optimization #devops

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So how can an enterprise take advantage of containerization to tackle complexity and not end up with even more complexity? This article provides some of the best practices that you can implement to adopt Kubernetes. https://lnkd.in/gsCbZVG5

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I just have gone through and Loved this Blog https://lnkd.in/ggx3F9UW on Cost Optimisation and technologies are covered. It highlights how dynamic cloud resources may be as well as how challenging it can be to manage prices. It consists of various cost-cutting tips, with an emphasis on EC2 instances in particular. Using savings plans, which can minimize expenses across your Amazon account, or moving from on-demand pricing to less expensive spot instances or reserved instances are some examples of these tactics. To cut expenses and simplify the processes, how we consistently optimize cloud resources for virtual machines, containers, and Kubernetes. To streamline and manage cloud infrastructure, it advises utilizing software that integrates with current AWS billing when subscribing through the AWS marketplace and top cloud platforms, services, and tools. #aws

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One of my beefs with terraform is it’s trying so hard to be flat. Some of us want very dynamic scripts. But when you create a k8s cluster, form the kubexonfig file, then need to use the kubexonfig file to load in the rest of the parts like ingress, having a depends_on would be nice for providers. I did cheat a little and abuse the variable system to force the provider to wait, but then you run into what about a workspace that will have kubernetes set to false and get a zero count for your k8s module? Then it gets angry because the module output isn’t there. I still like Chef. Chef let me do what I want when I want. Just was bad on creating the underlying infrastructure but great at configuring it once it was up. *shrug* #terraform #kubernetes #k8s #eks #automation #burgerkingmodel

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Want to get started with #Terraform and infrastructure as code (IaC)? Our very own Ryan Royals recently gave a great intro at the Adelaide #Azure User Group, and it is now available for you! Have a watch, put any questions below, and get started with Terraform. 😎 https://hubs.ly/Q02Bv5HL0

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Hi Folks, Here is today's Byte 💡: Azure Front Door Geo-Filtering Support 🚪 : 🔹Azure Front Door can now filter incoming traffic based on the geographical location, improving security and compliance. 🔹By allowing or denying requests from specific regions, organizations can better control access to their resources. 🔹Azure Front Door seamlessly integrates with other Azure services, such as VPN Gateway, VMs, and Storage Accounts. 🔹 Geo-filtering adds a scalable security layer without impacting the performance or availability of your applications. Area of Implementation 👨‍💻 : ➡ A multinational e-commerce company is required to comply with regional data residency regulations. ➡ With Azure Front Door's Geo-Filtering, they can restrict access to their services only to customers within compliant regions, ensuring they meet legal obligations while providing a secure and reliable shopping experience globally. Hope you find this Byte useful, do share your suggestions for any specific topic/concept 👍 Stay tuned for the next Byte... 🤓 #AzureBytes #azure #azurecloud #microsoft #microsoftbuild #microsoftinspire #microsoftlearn #azurefrontdoor #routing #cdn #dns #security #vpn #geofiltering Azure Developer Community OpsTree Solutions

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🚀Go Up or Go Out, Just Keep Driving Auto!🚀 Kubernetes offers two key autoscaling mechanisms for microservices: ⬆️ VPA (Vertical Pod Autoscaler) : - VPA automatically adjusts the CPU & memory requests for pods based on actual usage. - It’s great for handling resource-heavy or fluctuating workloads where scaling up (adding more resources) is more effective than scaling out (adding more pods). - You have resource-intensive services or unpredictable resource demands. - You want to adjust resource allocations without adding more pods. ✅Pros: - Adjusts resources based on actual needs. - Prevents resource starvation. ❌Cons: - Doesn’t scale the number of pods. - Requires pod restarts for changes to take effect. (In-place updates*) ➡️ HPA (Horizontal Pod Autoscaler) - HPA scales the number of pod replicas based on metrics like CPU or memory usage. - It’s ideal for handling fluctuating traffic by adding more pods as demand increases. - Your microservices are stateless and can scale horizontally. - You need to handle varying traffic or spikes in load. ✅Pros: - Scales out pods to handle load. - Great for stateless applications. ❌Cons: - Can strain resources if pods aren’t properly provisioned. - Can be complex to configure with custom metrics. For the best results, combine VPA and HPA. VPA ensures that each pod has the right resources, while HPA scales the number of pods as traffic increases. This dual approach optimizes both resource allocation and capacity. Often, combining both gives you the most efficient and resilient microservices setup on Kubernetes. #Kubernetes #VPA #HPA #Microservices #CloudComputing #Autoscaling #DevOps #Resiliency #Performance

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