Jemish Dobariya– DevOps Engineer | Acquaint Softtech
Are your deployments causing delays or production issues?
Meet Jemish Dobariya, a DevOps Engineer with 3+ years of experience in building reliable, scalable, and automated infrastructure. He ensures smooth deployments, minimal downtime, and stable system performance using tools like Docker, Kubernetes, AWS, Terraform, Jenkins, and Ansible.
🎥 Watch full video:
https://youtube.com/shorts/PinMilW5Juo?si=rNJqnYugZq7SDlX4
Objective 703.2 of the Linux Professional Institute (LPI) DevOps Tools Engineer 2.0 exam covers Basic Kubernetes Operations, a key part of modern #DevOps. 🖥️⚙️
Explore this exam objective with Fabian Thorns and Uirá Ribeiro: https://lpi.org/ladd
#LPI #kubernetes #devops #cloudnative #containerorchestration #devopsengineer
🚀 DevOps skills are becoming essential for modern software development.
Companies rely on tools like Git, Jenkins, Docker, Kubernetes, and Terraform to automate software delivery and manage cloud infrastructure.
Because of this demand, many developers and IT professionals explore DevOps Training in Electronic City Bangalore to gain experience with CI/CD pipelines and container technologies.
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Software virou infraestrutura social. Ele está no banco, no hospital, no transporte, no comércio, na escola, no governo e mais...
#computer #computador #Technology #tecnologia #software #softwaredevelopment #softwareengineer #softwaredeveloper #DesenvolvimentoDeSoftware #engenharia #engenhariadesoftware #softwaretesting #segurancadigital #AppSecurity #devops #DevOpsEngineer #desenvolvimentoweb #mobile #computerscience #cienciadacomputacao
https://www.moprius.com/2026/01/engenharia-de-software-moderna.html
I hear some people are slightly hesitant to use their tools.
Something about trust?
All the 🪿 I know are really well behaved. They love ✏️ and ✅. Write good notes when you show them where the information is. Brilliant little abductionists too if you need help finding a problem.
Have y'all met developers? Been into the bathoom at re:Invent?
The point is, the substrate provides the trust. They can't take an action you haven't provided them. Once it's exposed, what's the difference between a 🪿 running it because it appears to be the correct thing to do and a 🌀👩🏻💻 doing the same because it appears to be the correct thing to do.
That's on you BTW 🪞 you built the system, you made the wrong choice both available and obvious
In Wanderland, everything is logged with context. If they make a bad choice:
a) we know they've done it
b) we know why
How many 🌀👩🏻💻 you know can tell you why they've done something after that something has taken production ⬇️
Hello friends!
We're looking for multiple people to join my team at AOE Group working on Kubernetes-based Platform Engineering and Open Source:
- Fully remote possible or on-site in Wiesbaden
- In-House Platform project with focus on Kubernetes and Open Source
- #DevOpsEngineer https://jobs.aoe.com/en/job/devops-engineer-m-f-d.html
- #PlatformEngineer https://jobs.aoe.com/en/job/platform-engineer-f-m-d.html
- #Go / #Kubernetes expert https://jobs.aoe.com/en/job/kubernetes-docker-expert-m-f-d.html
Deploying in prod again?
Might as well look good doing it.
Funny DevOps shirts for people who break things professionally.
https://techgeeksapparel.com/devops-t-shirts
#DevOpsShirts #CI_CD #devops #DevOpsLife #devopsengineer #FunnyTechApparel #NoDeployFridays
Discord has evolved from a gaming-focused communication tool into a versatile platform supporting diverse online communities. Despite its large user base and active public servers, academic research on Discord remains limited due to data accessibility challenges. This paper introduces Discord Unveiled: A Comprehensive Dataset of Public Communication (2015-2024), the most extensive Discord public server's data to date. The dataset comprises over 2.05 billion messages from 4.74 million users across 3,167 public servers, representing approximately 10% of servers listed in Discord's Discovery feature. Spanning from Discord's launch in 2015 to the end of 2024, it offers a robust temporal and thematic framework for analyzing decentralized moderation, community governance, information dissemination, and social dynamics. Data was collected through Discord's public API, adhering to ethical guidelines and privacy standards via anonymization techniques. Organized into structured JSON files, the dataset facilitates seamless integration with computational social science methodologies. Preliminary analyses reveal significant trends in user engagement, bot utilization, and linguistic diversity, with English predominating alongside substantial representations of Spanish, French, and Portuguese. Additionally, prevalent community themes such as social, art, music, and memes highlight Discord's expansion beyond its gaming origins.
Parallel functional array languages are an emerging class of programming languages that promise to combine low-effort parallel programming with good performance and performance portability. We systematically compare the designs and implementations of five different functional array languages: Accelerate, APL, DaCe, Futhark, and SaC. We demonstrate the expressiveness of functional array programming by means of four challenging benchmarks, namely N-body simulation, MultiGrid, Quickhull, and Flash Attention. These benchmarks represent a range of application domains and parallel computational models. We argue that the functional array code is much shorter and more comprehensible than the hand-optimized baseline implementations because it omits architecture-specific aspects. Instead, the language implementations generate both multicore and GPU executables from a single source code base. Hence, we further argue that functional array code could more easily be ported to, and optimized for, new parallel architectures than conventional implementations of numerical kernels. We demonstrate this potential by reporting the performance of the five parallel functional array languages on a total of 39 instances of the four benchmarks on both a 32-core AMD EPYC 7313 multicore system and on an NVIDIA A30 GPU. We explore in-depth why each language performs well or not so well on each benchmark and architecture. We argue that the results demonstrate that mature functional array languages have the potential to deliver performance competitive with the best available conventional techniques.
Could This Be Automated?
Task: Manual database updates
Me: "This could probably be automated…"
🔗 https://techgeeksapparel.com/this-could-probably-be-automated-t-shirt/
#ITAutomation #DevOpsEngineer #CloudComputing #TechHumor
This Could Probably Be Automated T-Shirt: If you work in DevOps, cloud engineering, or software development, you know that every repetitive task should be
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