Devops latest news and discussion articles on Techminis

A naukri.com initiative

New

Home

Devops News

Dev

Image Credit: Dev

5 Awesome Docker Tools To Make Your Life Easier

Lazy Docker is a terminal UI for Docker and Docker Compose that makes managing containers easy.
Sliplane is a hosting platform for deploying Docker containers with features like push-to-deploy, zero-downtime deployments, and built-in logging and monitoring.
Dive is a tool for exploring and analyzing Docker images layer by layer, helping identify ways to optimize image size and save disk space.
Orbstack is a Docker desktop alternative for macOS that is faster and less resource intensive.
Watchtower is a tool that automatically updates Docker images to the latest version for easy maintenance.

Read Full Article

3 Likes

Dev

352

Image Credit: Dev

Ansible Playbooks for Infrastructure Automation

Automate important, repetitive tasks with these essential Ansible playbooks.
Playbooks cover tasks such as server provisioning, web server setup, database configuration, user and permission management, firewall configuration, backup and restore, system update and patch management, application deployment, monitoring setup, and disk space cleanup.
Sample tasks for each playbook are provided.
Each playbook is designed to simplify infrastructure management tasks.

Read Full Article

21 Likes

Dev

247

Image Credit: Dev

Build a Chatbot to streamline customer queries and automate tasks integrating amazon Lex and Bedrock

This article discusses how to build a chatbot to answer user queries and automate tasks like booking travel tickets using Amazon Lex, AWS S3, Amazon Bedrock, Amazon Polly, and AWS IAM. The chatbot is personalized to accept company data and operates with a knowledge base.
The first step is to create a Lex Bot by entering the company information and intents like BookJourney, CheckReservationDetails, GetTravelStatus, CancelJourney, RescheduleJourney, and FallbackIntent.
Once the Lex bot is created, create an S3 bucket and store company data like services, prices, schedules, complimentary meals, and customer service.
Create a knowledge base for Amazon Bedrock and sync the PDF documents from the S3 bucket. Then create a Lex bot QnA intent using the knowledge base for Amazon Bedrock.
Test the chatbot by running a few queries and verifying that the bot is working as expected. Build a Web UI and attach it to the website to access the chatbot.
Create a version and alias for the chatbot and create a CloudFormation stack by entering the bot ID, alias ID and other required parameters.
Copy the code snippet from the output and paste it into the website's HTML body section. Open the website, test the chat icon, and observe the chatbot's operation by booking tickets and asking questions.
The training process for the chatbot involves configuring every slot to look for assistance from the knowledge base. For instance, configuring the BookJourney intent means configuring a departure city prompt and enabling assisted slot resolution.
Adding more information to the company just involves uploading the new PDF document to S3 and syncing the data source for the knowledge base to read it.
In conclusion, this article gives a step-by-step guide on building a chatbot for businesses to eliminate long wait times and reduce operational costs by automating tasks like booking tickets, canceling, rescheduling, and providing quick responses to FAQs.

Read Full Article

14 Likes

The New Stack

244

Image Credit: The New Stack

How Kubernetes Memory Requests and Limits Actually Work

Understanding the inner workings of Kubernetes resource management involves achieving an end-to-end contextual understanding of how resource management functions including everything from its user abstractions to technical implementation at the Linux kernel level.
Kubernetes pods get scheduled on nodes purely based on their requests. Node “fullness” is request-based, ignoring usage and limits.
For memory resources, there’s no cgroup setting corresponding to the memory request abstraction.
CPU time can be withheld or deferred without terminating the process, though doing so might hurt performance. But when it comes to memory, you either get it or you don’t. There is no try and there is no defer.
When you set a memory limit in Kubernetes, all the container runtime does is plug that number straight into the memory.max control for the container’s cgroup. If the in-use memory for the cgroup exceeds that limit, the OOMKiller will smite it.
Kubernetes does not set any cgroup controls based on memory requests.
Kubernetes won’t run any new pods on a node if the sum total of the running container memory requests would add up to more than the node’s allocatable memory.
The OOMKiller is a Linux kernel feature invoked when a node runs out of physical memory.
Kubernetes sets the oom_score_adj for every container process it starts and it uses clever math to ensure that containers using more memory than they requested will always be terminated before well-behaved containers.
Making a reasonable decision about which process to kill when something needs to be killed is great, but ideally, we want to avoid having to ever make that decision in the first place.

Read Full Article

14 Likes

The New Stack

213

Image Credit: The New Stack

Pulumi Centralizes Kubernetes Management with Native Tools

Pulumi has launched new tools and features to simplify and secure Kubernetes deployments.
The Infrastructure as Code (IaC) platform offers a Kubernetes-native deployment agent for improved security and scalability.
Updates include a Pulumi Kubernetes Operator 2.0, improved Amazon Elastic Kubernetes Service (EKS) provider, Pulumi ESC integration with External Secrets Operator, and Pulumi Insights for unified search and compliance remediation.
Customer-managed Pulumi Deployments Agents can now be hosted within Kubernetes environments, providing greater flexibility and control over infrastructure deployments.

Read Full Article

12 Likes

Hashicorp

345

Image Credit: Hashicorp

Fix the developers vs. security conflict by shifting further left

Collaboration between development and security teams can become difficult and lower efficacy of cloud security, due to the constant tension between developers and security teams over conflicting toolchains and manual reviews. It is difficult to get both teams to operate from the same playbook, so platform teams are key in removing conflicting toolchains in order to improve this. The 'shift-left' movement is now focusing on shifting left through tools instead of only culture or skilling, by embedding policies into templates and making sure all reinforced policies and best practices are taken care of before any code and applications make it through to production. Modern Infrastructure Lifecycle Management (ILM) adheres to this and Security Lifecycle Management (SLM), which aims to manage the most sensitive data, especially secrets/credentials, from creation to expiration or revocation. Establishing a standardised shared service with an automated workflow is key with tools such as Hashicorp Terraform being a popular method of implementation. Hashicorp's Infrastructure Cloud has also played a critical role in modern SLM practices with its successful implementation by companies such as Canva.
Nearly two-thirds of CISOs and developers agree that a lack of communication and collaboration is a problem in implementing better software supply chain security. Tooling is one of the main areas of disagreement, with developers suggesting that their security team's requirements interfere with productivity. This emphasizes the importance of platform teams removing one of the key obstacles; conflicting toolchains that cause inefficiencies and introduce vulnerabilities. Platform teams play an important role in solving these impedance issues, they can eliminate the friction between teams and enable the quick and easy deployment of apps. The infrastructure of cloud security should have security baked-into various templates developers use to start a project.
The shift-left movement, which began as an attempt to fix friction between developer and security teams when quality assurance and security checks were only conducted at the end of an application's development lifecycle, has now evolved to include shifting left through embedding policies and best practices before any code or applications make it through to the production environment.
By using platforms, such as Hashicorp's Terraform and Hashicorp's Vault, infrastructure lifecycle management (ILM) can become systematic and repeatable, thus fostering a standardized infrastructure management process with curated self-service workflows and tools. Meanwhile, Security Lifecycle Management (SLM) is all about secrets management to secure sensitive credentials and impulsively enable encrypt data during transit.
With a strong focus on cloud security and the developer experience, modern platforms need tools that foster secure and consistent workflows which support all teams participating in the delivery pipeline.
HashiCorp's tools, such as Terraform and the Lifetime Cloud, have become trusted ILM and SLM partners for many customers and have successfully helped companies reduce friction between security and development teams, establishing an efficient, golden developer path.
An effective cloud security program eliminates friction, enables reproducibility, and establishes infrastructure automation, eliminating many of the common friction points between security and dev teams that hinder production speed and time to market.
Central secrets control planes, access control lists limiting lateral movement, dynamic credentials, encryption, and auditing are important SLM components that ensure an effective, scalable secrets management platform is in place. HashiCorp Vault is a popular tool for many companies.
Misaligned priorities, mismatched tools, and inconsistent workflows are the precursors of friction between security and development teams. It is essential that they work in unison to prevent security breaches while increasing productivity and efficiency.
To eliminate friction, accelerate production, and reduce risk costs, it is important to streamline the dev and security collaboration.
The Infrastructure Cloud can help organisations shift left by taking the burden of implementing security requirements from development teams and removing friction points between security and dev teams. To learn more about this, read our white paper available from the article's resource section.

Read Full Article

20 Likes

Solarwinds

Image Credit: Solarwinds

4 Takeaways from the SolarWinds State of ITSM Report

The SolarWinds State of ITSM Report analyzed over 2,000 ITSM systems and more than 60,000 data points.
The number of service desk agents doesn't significantly impact issue resolution time.
Implementing automation saves an average of three hours per ticket.
Teams using SLAs resolve tickets two hours faster on average.

Read Full Article

2 Likes

Dev

194

Image Credit: Dev

Deep Dive 🤿: Where Does Grype Data Come From?

Grype is an open source vulnerability scanner for container images and filesystems.
The tool compares the software packages in an image against a database of known vulnerabilities.
Grype relies on upstream data providers to obtain vulnerability data.
The providers include Alpine, Amazon, Debian, GitHub Security Advisories, NVD, Oracle, RedHat, SLES, Ubuntu, and Wolfi.
Grype uses vunnel and grype-db open-source tools to build its vulnerability.db database.
The vulnerability.db file can be built manually if you want to use only a subset of upstream sources or create a custom database.
The file has five tables, but only two tables store significant data: vulnerability_metadata and vulnerability.
Ubuntu, NVD, and Susa have the most entries in the vulnerability_metadata table.
The data in the vulnerability.db file can be helpful in platform security and broader CVE trends analysis.
In conclusion, Grype's open data pipeline makes its vulnerability.db more flexible and useful.

Read Full Article

11 Likes

Siliconangle

346

Image Credit: Siliconangle

Cast AI introduces AI Enabler and zero-downtime live migration for Kubernetes workloads

Cast AI introduces AI Enabler and zero-downtime live migration for Kubernetes workloads
AI Enabler optimizes deployment of large language models, reducing operational costs.
Commercially Supported Container Live Migration ensures zero-downtime migrations for stateful workloads on Kubernetes.
The tool and feature help optimize infrastructure usage, reduce costs, and maintain continuous uptime.

Read Full Article

20 Likes

Siliconangle

354

Image Credit: Siliconangle

ScaleOps raises $58M to accelerate Kubernetes configuration automation

ScaleOps Labs has raised $58m in a Series B round led by Lightspeed Venture Partners, with participation from existing investors NFX and Glilot Capital Partners, and new participant Picture Capital. Since finalising its Series A round 11 months ago, the firm raised $80m overall. ScaleOps provides a cloud resource management platform that can help enterprises save up to 80% on Kubernetes application deployments costs.
Kubernetes, an open-source container orchestration tool, is used to manage modular components of cloud-based applications. However, coordinating Kubernetes applications currently involves manually adjusting resource consumption, a process ScaleOps aims to automate with AI. Two new features being added to its platform will speed up cost savings by 50% and improve application performance.
Kubernetes' scalability problems stem from the difficult process of managing and maintaining Kubernetes environments; the resource configurations often used are largely static and do not reflect current needs, meaning teams can spend hours adjusting them manually to ensure they avoid under or over-provisioning cloud resources consumed by their apps.
ScaleOps automates this process with AI, allowing Kubernetes deployments to be managed and their configurations to be adjusted based on demand. This ensures every app has optimal resources to run without performance problems while maintaining cost control. The software can be integrated with cloud platforms like AWS, Microsoft Azure and Google Cloud and on-premises environments.
New customers since the last funding round include Fortune 100 firms such as Cato Networks, SentinelOne and Wiz Inc.
Two new capabilities added to the ScaleOps platform to accelerate cost savings include AI-powered predictive scaling in real-time and intelligent pod placement. These can additionally promote application performance while delivering up to 50% additional cloud cost savings.
ScaleOps co-founder and CEO Yodar Shafrir said the firm aims to provide a solution that seamlessly automates cloud resource management in real-time, and added that no one in the market was solving the problem.
David Gussarsky, from Lightspeed Venture Partners, praised ScaleOps as the clear category leader in cloud resource management and its automation abilities as a breakthrough. He added that their rapid growth over the past year underlines the critical nature of fulfilling the market's needs.
The new funding and capabilities come just 11 months after the firm secured its Series A funding.
ScaleOps' platform allows enterprises to save up to 80% on Kubernetes application deployment's costs.

Read Full Article

21 Likes

Sdtimes

327

Image Credit: Sdtimes

What’s new from KubeCon + Cloud Native Con North America 2024

Red Hat introduces new AI capabilities to its internal developer platform Red Hat Developer Hub to harness the power of AI and deliver smarter applications and services to their customers and end-users.
Observe launches Kubernetes Explorer, a tool designed to simplify visualizing and troubleshooting for cloud-native environments, enabling DevOps teams and software engineers to easily resolve issues more quickly.
Komodor extends its existing Kubernetes management capabilities to include the full ecosystem of K8 add-ons and enables visualization, operation, detection, investigation, remediation, and optimization of all the components in Kubernetes clusters.
Mezmo unveiled Mezmo Flow, a guided experience for building telemetry pipelines, simplifying both developer and SRE workflows for next-generation log management.
Tigera revealed several new features for Calico, including network security and runtime security updates, extending its network security and visibility capabilities to virtual machines and hosts and providing new enhancements for implementing network security.

Read Full Article

19 Likes

Dev

327

Image Credit: Dev

Turning Ideas into Art: Texas Animation Studios You Should Know

Texas has developed a reputation for transforming unique ideas into captivating visual art in the world of animation.
Texas animation studios have become known for pushing the boundaries of traditional animation, creating highly detailed, realistic 3D animations and stunning visual effects.
Innovative technology, diverse storytelling techniques, and industry experience are a few standout elements that set animation studios in Texas apart.
Texas studios offer creative solutions for businesses seeking new ways to connect with their audiences through animated explainer videos, product demonstrations, and branded characters.
They have also become a top destination for educational animation with Texas studios creating content for online courses, training programs, and even school curriculums.
In healthcare, animation is an invaluable tool for illustrating procedures, explaining complex medical concepts, and training medical professionals.
One key strength of Texas animation studios is their commitment to collaboration, both within the studio and with their clients.
If you’re considering working with an animation studio in Texas, start by identifying the type of animation you need.
Texas is poised to continue leading the way in animation, with studios that blend technical skill with artistic innovation.
For anyone seeking fresh, compelling animation work, Texas studios represent a perfect blend of artistry, technological know-how, and professionalism.

Read Full Article

19 Likes

Medium

307

Image Credit: Medium

Creating an automated, source-controlled deployment pipeline for Jenkins Controllers

The stability of a Jenkins controller is crucial, especially when it has become so crucial to everyone’s daily workflow
Setting up a staging environment was not practical, so a reliable way to fully mirror each job's settings or configs was needed.
Replicating the configuration was achieved by using XML files to copy job configs into the Jenkins Controller Repro.
The source-controlled deployment pipeline allowed for changes to be tested in a replica of the production environment before going live.

Read Full Article

18 Likes

Dev

304

Image Credit: Dev

The Benefits of MedOne and VMware: A Cloud Solution Built for the Future

The partnership between MedOne and VMware offers businesses a powerful and flexible cloud solution.
Key benefits include seamless virtualization with VMware vSphere, cost savings, simplified IT management, and increased flexibility.
Consistent hybrid cloud with VMware Cloud Foundation enables integrated management of on-premise and cloud environments, smooth workload migration, and improved security.
Enhanced security and automation are achieved with VMware NSX, providing automated network management, micro-segmentation, and comprehensive security policies.

Read Full Article

18 Likes

Siliconangle

214

Image Credit: Siliconangle

Nutanix offers cloud-native AI deployment platform with predictable pricing

Nutanix Inc. is launching a cloud-native AI infrastructure platform called Nutanix Enterprise AI.
The platform can be deployed on any Kubernetes installation, including public cloud services.
Nutanix Enterprise AI provides a consistent multi-cloud operating model that can significantly reduce the deployment time of AI applications.
The offering is aimed at data scientists, simplifying the deployment of generative AI models.

Read Full Article

12 Likes

For uninterrupted reading, download the app

Devops News

Discover more