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Kubernetes, Rust, Linux and DOS? The Year in Open Source

Elasticsearch and Redis dominated discussions surrounding open source licensing changes.
Kubernetes celebrated its 10th anniversary.
Linux remained a crucial part of the tech landscape, with 4.55% of desktops running on it.
Rust was seen as key to bringing memory safety to codebases.
Funding remains a significant challenge for open source developers, with 86% of investment still based on employee contributions.
Microsoft open sourced the 1988 code for MS-DOS 4.0.
FreeDOS celebrated its 30th anniversary, with developer Jim Hall sharing lessons learned about grounding projects in community and communication.
New open source projects included the Dillo web browser and the Eclipse Foundation's Theia IDE.
GitHub released the Secure Open Source Fund in November, with American Express, Microsoft, Shopify, and Stripe among its initial donors.
The open source movement continued to grow and evolve, with an ever-increasing community of satisfied users.

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Solarwinds

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SolarWinds Voices: Sudhakar Ramakrishna on InformationWeek

SolarWinds CEO Sudhakar Ramakrishna spoke with InformationWeek on building trust and improving relationships.
Ramakrishna emphasized the importance of not taking customer trust for granted.
He discussed how SolarWinds regained trust through transparency and taking responsibility for the 2020 incident.
The full interview can be read on informationweek.com.

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Dev

10h

311

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Custom Resource Definitions (CRDs) in Kubernetes: Extending the API for Custom Resources

Custom Resource Definitions (CRDs) allow users to extend the Kubernetes API by defining their own custom resources, which better automation, monitoring, and scaling of your applications.
A Custom Resource Definition (CRD) is a way to extend Kubernetes with new types of resources that behave like native Kubernetes resources.
Once you create a CRD, Kubernetes will treat it as a new API resource type.
Creating a CRD involves defining the Custom Resource Definition, applying the CRD to the Kubernetes Cluster, and creating Custom Resources.
You can define complex validation schemas for your CRDs using OpenAPI v3 schemas.
CRDs can be used in conjunction with Kubernetes Controllers to manage the lifecycle of custom resources.
Best Practices for CRDs include proper versioning, using namespaces for isolation, defining defaults, avoiding complex and large schemas, and using OpenAPI validation.
CRDs enable developers to take full advantage of Kubernetes' extensibility to fit specific use cases.
CRDs allow you to integrate your application resources into Kubernetes' declarative management model, which enables better automation, monitoring, and scaling of your applications.
With CRDs, developers can manage and model domain-specific resources while using the same Kubernetes tools and processes as native resources.

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Dev

10h

164

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Kubernetes Cluster Federation and Multi-Cluster Management: Simplifying Distributed Cluster Operations

Kubernetes Cluster Federation and Multi-Cluster Management enable organizations to manage multiple Kubernetes clusters as a single entity, allowing them to deploy and manage workloads, configurations, and policies across a federated set of clusters.
Kubernetes Federation provides Federated Clusters, Federated Resources, Control Plane, and Federation API to improve consistency in deploying applications across multiple clusters.
Federation allows you to replicate workloads across multiple clusters, ensuring that your applications are highly available, even if one or more clusters fail. It also provides a single control plane to manage resources across multiple clusters, simplifying management, monitoring, and troubleshooting.
However, managing multiple clusters, each with its own configuration and lifecycle, can add significant complexity to your infrastructure. Ensuring reliable and low-latency communication between federated clusters can be difficult, especially if the clusters are geographically distributed. While some features are not yet fully supported across all Kubernetes resources, new features may take time to stabilize.
Multi-Cluster Management tools provide another way to manage multiple Kubernetes clusters across regions and cloud providers. These tools typically focus on simplifying the management of workloads, security, and monitoring across clusters.
Some popular Multi-Cluster Management tools include Rancher, Anthos (by Google Cloud), Red Hat OpenShift, Kubefed, and Kubernetes Cluster API.
To effectively manage Kubernetes clusters across multiple regions or cloud environments, organizations should consider cluster isolation, centralized monitoring, automated cluster operations, federating critical resources only, using network policies and service mesh, and data and state management.
Kubernetes Cluster Federation and Multi-Cluster Management are key solutions for managing large-scale Kubernetes environments that span multiple regions, data centers, or cloud providers. Both approaches provide benefits like high availability, disaster recovery, and geographical distribution, but also come with challenges that require careful consideration and planning.

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Dev

16h

341

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What is infrastructure as code and how its transforming DevOps

Infrastructure as code (IaC) is the ability to provision and support computing infrastructure using code instead of manual processes and settings.
IaC automates infrastructure deployment and configuration processes, making them consistent, repeatable, and version-controlled.
DevOps teams integrate infrastructure as code (IaC) into continuous integration and continuous deployment (CI/CD) pipelines to automate infrastructure tasks.
IaC revolutionizes DevOps by providing consistency and standardization, speed and agility, version control, collaboration and automation, cost efficiency, disaster recovery and scaling, and real-life impact on DevOps.

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Medium

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Transforming Engineering: From Cost Center to Strategic Partner

The article builds on the author's reflections from a previous article that focuses on crossroads in technology leadership and digital transformation.
Leadership enters a coaching program called The Extraordinary Leader, where feedback is given on driving business results.
Leadership should focus more on driving business results in technology-led innovation.
Technology-driven innovation should communicate impact by adopting value stream management and transitioning to a product operating model to deliver meaningful results.
The two pillars for transforming engineering are code is not the product, and value that code brings to the product is the product.
The greatest challenge for a technology leader is communication, translating technical initiatives into business language, customer retention, revenue growth, operational efficiency, etc.
Alignment between technical efforts and business priorities ensures that engineering is seen as a strategic partner, not just a cost center.
Embedding outcomes into engineering work reflects the integration of Value Stream Management principles with the product operating model.
Preventing layoffs begins by minimizing reactive hiring sprees, optimizing the size and allocation of the right mix of resources for added value.
Leadership should link technology investments to business results as a way to showcase its essential contribution to organizational growth and resilience.

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Devopsonline

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Key AI Predictions within the growth and sustainability sector

Data centres will face mounting pressure to reconcile AI’s surging energy requirements with strict sustainability goals.
Companies that initially rushed into AI will reevaluate its financial and energy impact, shifting towards selective, high-value applications.
Digital twins will be essential for data centres to meet AI goals sustainably and manage power, renewable sources, and cooling measures.
EU's 2025 Energy Efficiency Directive will prompt data centre accountability and drive greener practices and adoption of tools like digital twins.

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Dev

10h

307

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Using Kubernetes Labels, Annotations, and Taints for Effective Resource Management

Labels, annotations, and taints are powerful mechanisms for organizing, identifying, and controlling how workloads are scheduled and managed across clusters.
Labels are used primarily for organizing, grouping, and selecting resources in the Kubernetes cluster.
Annotations hold additional, often non-queryable, information that is useful for human operators or tools.
Taints allow you to mark a node so that no pods will be scheduled onto it unless the pod has an explicit toleration.
Labels, annotations, and taints are essential to manage Kubernetes resources effectively.
Taints are convenient for node resource management and controlling pod placement in Kubernetes.
Use labels to group related resources together and ensure consistency across resources.
Annotations store important metadata like change logs, revision history, and links to documentation.
Use taints when you need to prevent pods from being scheduled on certain nodes unless explicitly tolerated.
By using labels, annotations, and taints in a coordinated manner, you can optimize resource management in your Kubernetes clusters, improving scalability, reliability, and efficiency

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Dev

10h

235

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Monitoring Containerized Applications with Kubernetes Tools: A Comprehensive Guide

In the world of containerized applications, monitoring is critical to ensure the performance, availability, and health of both the infrastructure and the applications running within Kubernetes clusters.
Key areas of monitoring include cluster health, application performance, resource usage, and alerts and anomalies.
Kubernetes provides a variety of native tools and third-party integrations to effectively monitor containerized applications.
Core components of Kubernetes monitoring are Metrics Server, Prometheus, Grafana, Kubernetes Dashboard, Fluentd/ELK Stack, and Jaeger/OpenTelemetry.
Prometheus is the most popular tool for monitoring Kubernetes environments. It collects and stores metrics from containers, services, nodes, and Kubernetes components.
Grafana is a powerful visualization tool that works seamlessly with Prometheus to visualize Kubernetes metrics.
The Kubernetes Dashboard is a web-based UI that helps you visualize the health of nodes, pods, deployments, and services.
Fluentd and ELK Stack are used for centralized logging. Fluentd collects logs from Kubernetes containers and sends them to Elasticsearch for storage. Kibana is then used to analyze and visualize logs.
Jaeger is used for distributed tracing, allowing you to trace requests as they travel through multiple microservices or components.
Best practices for Kubernetes monitoring include monitoring cluster resources, setting up alerts, centralizing logging, implementing distributed tracing, being mindful of retention and scaling, using pre-built dashboards, and optimizing metrics collection.

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Dev

10h

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Configuring Node Taints and Tolerations in Kubernetes: A Guide to Fine-Grained Pod Scheduling

Kubernetes provides a powerful scheduling mechanism that helps ensure workloads are placed on the most appropriate nodes.
Taints and tolerations allow for finer control over where Pods are scheduled within a Kubernetes cluster.
A taint is applied to a node and prevents Pods from being scheduled on that node unless the Pod has a matching toleration.
A toleration is applied to a Pod and allows it to be scheduled on nodes that have matching taints.
Some use cases for taints and tolerations include reserving nodes for specific workloads, evicting Pods from unhealthy nodes, and ensuring resource isolation.
To apply a taint to a node, use the 'kubectl taint' command. To add a toleration to a Pod, include it in the Pod specification.
The 'NoExecute' taint is useful for evicting Pods from a node when it becomes unhealthy.
Best practices for taints and tolerations include using them for specific workloads, avoiding overuse, and combining them with affinity/anti-affinity rules.
Overall, taints and tolerations are a powerful feature in Kubernetes that can enhance the efficiency and flexibility of your cluster.

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2 Likes

Dev

19h

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Day 23: Docker Resources

Julia Evans' zine about containers is an absolute gem! It's a fun, illustrated guide that breaks down complex container concepts into digestible pieces.
The official Docker documentation is your comprehensive guide to all things Docker.
For those interested in the deeper technical aspects, Docker's source code is available in two main repositories: BuildKit and Moby.
The Open Container Initiative (OCI) Specification defines the industry standards for container formats and runtimes.

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Dev

20h

260

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Terraform: Steps to create complete AWS S3 module

Terraform enables users to simplify the process of organizing and reusing infrastructure code by creating modules.
Using Terraform modules becomes important in cases where users need to reuse infrastructure code across different projects.
Step 1 involves setting up the module structure to keep the Terraform code organized and maintainable.
Step 2 involves defining the core resources for the module in the main.tf file.
Step 3 requires defining the input variables for the module in the variables.tf file.
Step 4 involves defining the required providers and their respective versions in providers.tf.
Step 5 involves defining the output values that will be exposed by the module in outputs.tf file.
Step 6 involves using the Terraform module in the root configuration by defining the values for the variables.
Creating a Terraform module helps organize code and define reusable components, such as managing S3 buckets with advanced features like versioning, encryption, and policies.
Terraform modules can be used to minimize duplication, encapsulate logic for a group of resources, and follow best practices.

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15 Likes

Medium

21h

309

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Jenkins-out CircleCI-in : Does It Worth To Switch Over ?

Jenkins has been widely used for CI/CD processes for many teams and projects.
Migrating from Jenkins to a more modern CI/CD tool like CircleCI can be beneficial.
CircleCI allows local installation of its CLI for debugging and iterating on pipelines.
CircleCI also allows running jobs locally, providing convenience and ease of use.

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18 Likes

Medium

21h

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Engineering’s Business Value: From Black Box to Clarity

Technology has traditionally been viewed as a cost center and impacted by layoffs and reduction-in-force initiatives, but Value Stream Management (VSM) practices can address the challenge of linking and communicating the ROI of engineering investments.
VSM aligns work with value streams that deliver measurable business and customer outcomes for accurate tracking of costs, ROI, and value delivery at the team and product level.
Modern organizations are solving cost reduction challenges through intentional team design, using stable, cross-functional teams with dedicated software engineers and selective sharing of specialized roles across a limited number of teams.
Defining clear, measurable outcomes and improving visibility can help establish frameworks that articulate the tangible value technology brings to the business, address unnecessary overhead, and avoid layoffs caused by poor resource planning.
Technology success stems from excelling in two core areas: flow and realization. Structured OKRs can bridge these areas by translating organizational strategy into team-level objectives and ensuring every technical effort connects directly to business outcomes.
Success lies in whether work delivered creates valuable outcomes and the ability to gain insights even when results fall short of expectations, empowering teams to refine their approach or pivot entirely.
Starting with anticipated outcomes enables teams to develop meaningful OKRs that align with broader strategic objectives, define clear customer-centric goals and connect directly to the organization’s strategic direction.
Measurable business features and technical debt investments, when linked to specific outcomes, become strategic initiatives with identifiable business value, rather than “mysterious maintenance work”.
By documenting both anticipated and actual outcomes at the epic level, teams can refine their approach and make strategic decisions that drive growth, while justifying investments and creating a roadmap for long-term success.
By closing the gap between investment and impact, organizations can transform how they view technology, from a cost center to a catalyst for innovation, growth, and customer satisfaction.

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5 Likes

Medium

21h

111

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Profitable Engineering: Linking Software Engineering to Business Results

This three-part series aims to show a direct connection between software engineering and business results.
It provides practical insights and strategies to shift the perspective of technology as a cost center.
The articles cover topics such as redefining the value of technology, evolving engineering as a strategic partner, and shifting towards delivering meaningful outcomes.
The series encourages readers to transform their approach and align technology with measurable outcomes.

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