A reliable release process
CI/CD, builds and tests, configuration management and versioned releases. We also define how to roll back when a release goes wrong.
BUILT TO RUN
DevOps Consulting: CI/CD, Kubernetes and Cloud
The code is ready. Now it needs to run.
We bridge the gap between development and the environment where your system lives: release pipelines, containers, infrastructure and operational visibility, built in a way your team can understand and reproduce.
Talk about DevOps, Cloud & InfrastructureTHE RIGHT FIT
This is a fit if…
- Teams with manual deployments that depend on one person.
- Systems moving to Azure, Kubernetes or OpenShift.
- Organizations that need to adapt a product to their infrastructure requirements.
A CLEAR DELIVERABLE
What you get along the way.
Infrastructure that fits
Docker, Kubernetes, Helm or managed cloud services as needed. Network, permission and data boundaries are defined explicitly.
Operability
Logs, metrics, health checks and documentation. We check how problems get detected and who is responsible for handling them.
HOW WE MOVE FORWARDWe map the path.
We map the path.
Then we move.
- 01
Review of deployment, dependencies and organizational constraints
- 02
Process design and infrastructure adjustments
- 03
Implementation and testing in a suitable environment
- 04
Documentation and knowledge transfer to the team
THE FULL PICTURE
Good DevOps consulting does not start with picking a tool. It starts with a simple question: what happens between the moment a developer merges a change and the moment it runs for your users, and who knows how to fix it when something breaks? This page explains what DevOps and cloud work looks like in practice, from CI/CD and Terraform to Kubernetes and cloud migration to Azure, how it is planned in stages, and how to choose who helps you.
What DevOps consulting is, and what it is not
DevOps is a way of working that connects the people who write code with the people who run it. In practice, builds, tests, deployments and infrastructure are defined as code, stored in a repository and reviewed like any other change. When it works, a release is routine, not a tense evening where everyone waits for the one person who knows how it is done.
DevOps consulting is the help that gets you there: assessing what exists, designing what is missing, implementing it alongside your team and transferring the knowledge so the system does not depend on the consultant. DevOps services can be a focused project, such as building a pipeline or moving to the cloud, or ongoing support while the infrastructure grows with the product.
You will also hear related terms such as Platform Engineering and SRE. The differences matter in large organizations, but at the consulting stage the practical question is the same: what is slowing the team down today, and what is the smallest step that would improve it?
What it is not: installing a popular tool because everyone else uses it, or building a complex platform that only its author understands. The goal is a system your team can explain, change and operate on its own.
Signs it is time for DevOps services
Most of these signs do not look urgent on their own. The problem is that they add up: every release takes a little longer, every incident needs a little more digging, and at some point the team starts avoiding changes so as not to break anything.
The need rarely shows up as a strategic decision. It shows up as daily friction that keeps piling up. If several of these sound familiar, it is probably time to stop and sort out the infrastructure:
- Deploying to production requires a manual checklist, or a specific person who must be available.
- The build passes for one developer and fails for another, or fails intermittently for no clear reason.
- There is no reliable way to roll back when a release goes wrong.
- Development, test and production environments differ, and nobody is quite sure how.
- Secrets, keys and passwords live in config files, chat messages or personal laptops.
- The cloud bill keeps growing, and it is unclear which resources are still in use or who created them.
- Production incidents are reported by customers rather than caught by monitoring.
- A startup preparing for its first enterprise customer is asked about environment separation, permissions and release process, and has no clear answer.
The layers of the work: from CI/CD to monitoring
DevOps services cover several layers that depend on one another. Not every project needs all of them, but it helps to understand how they connect before deciding where to start.
Order matters. Work usually starts with CI/CD and secrets management, because they affect every other layer, and only then moves on to orchestration, deeper monitoring and cloud cost optimization.
- CI/CD: automated builds and tests on every change, versioning and artifact management, and a release flow with approval gates and a defined rollback path. It can be built on GitHub Actions, Azure DevOps or the tooling you already have.
- Containers: packaging services with Docker so the same image runs in development, testing and production, with a proper registry and dependency management, for example in Nexus.
- Kubernetes: setting up managed Kubernetes such as AKS or working within OpenShift, including Helm, namespace separation, resource limits, health checks and gradual rollouts.
- Infrastructure as code: Terraform for networks, permissions and cloud resources, with managed state and a review process for every change, so any environment can be rebuilt.
- Cloud: designing an Azure environment or migrating an existing system to the cloud, including identities, permissions, networking and cost control.
- Security and configuration: secrets kept out of code, least-privilege access for pipelines and services, and scans that fit into the flow instead of blocking it.
- Operational visibility: logs, metrics and alerts that point to real problems, and documentation that explains what to do when they appear.
Kubernetes and cloud migration: when they make sense
Kubernetes is powerful, but it is also a system you have to operate: upgrades, networking, permissions, monitoring and failures that are hard to diagnose without experience. It fits best when you have several microservices that ship independently, real requirements for availability and changing load, or an organization already standardized on it. For a product with one service and a database, a simpler managed service may be the right call.
Cloud migration is not a single move either. Some systems can be moved almost as they are, some are worth repackaging into containers, and some components are better replaced with a managed service. The decision depends on the system's dependencies, security requirements, your team's skills and long-term operating effort, not just the monthly price of resources.
Azure cloud consulting usually centers on a few foundational decisions that are hard to change later: how environments are split into subscriptions and resource groups, how identities and permissions are managed, how the network is laid out and what is exposed to the internet, and how costs are tracked per team or service. When these decisions are documented and defined in Terraform from the start, adding a new service or environment becomes a small, predictable change rather than a project of its own.
DevOps for startups usually starts small and clean: one reliable pipeline, environments defined in Terraform and secrets handled properly. Complexity is added when the product justifies it. In larger organizations the challenge is different: fitting into existing rules such as closed networks, security approvals, internal registries and change management, without losing pace.
How the work runs, step by step
Project length depends on scope and starting point, but the structure is almost always the same. Each stage ends with something you can check, so it is always clear where things stand and what comes next.
In focused projects, such as a CI/CD setup for a single service, the stages are short and sometimes merge. In broader ones, such as a cloud migration or a Kubernetes rollout for several teams, implementation is split into waves by service or environment.
Assess the current state
Review the code, build and deployment flow, environments and permissions, and talk to the people who develop and operate the system. Mark where time is lost and where the biggest risks are.
Set goals and priorities
Decide together what must change first and what can wait, and choose metrics that will show whether the change actually worked.
Design the architecture and infrastructure
Choose tools and structure that fit your constraints, document the decisions and the rejected alternatives, and define network, permission and data boundaries.
Implement in increments
Build in small steps: start with one service or one environment and expand only after the previous step works and has been tested.
Test under real conditions
Run real releases, rehearse rollbacks, and check what happens when a component fails or a secret is rotated.
Document and hand over
Runbooks, diagrams and working sessions with the team, until someone on your team can ship a release and handle an incident without help.
What you get and how success is measured
At the end you should have something tangible: pipelines defined as code, infrastructure that can be rebuilt from Terraform, an up-to-date architecture diagram, operating documentation and a prioritized list of next steps. Everything stays with you, in your repositories and your accounts.
Beyond the technical deliverables, a record of the decisions matters just as much: why a tool was chosen, which alternatives were considered and what would need to change to reconsider them. That record saves repeated debates when new people join and lets you change direction deliberately as the product evolves.
Success is measured against the starting point, not against a feeling. The standard DevOps metrics work well here:
- Deployment frequency: how often you can release without special effort.
- Lead time from commit to production: how long an approved change takes to reach users.
- Change failure rate: how many releases need an urgent fix or a rollback.
- Time to restore: how quickly an incident is detected and service is back to normal.
- People dependency: whether more than one person can ship a release and handle an incident.
How to choose a DevOps provider, and mistakes to avoid
The common mistakes repeat themselves: choosing tools before understanding the problem, building infrastructure sized for a company several times larger, leaving all the knowledge with one person, even when that person is the consultant, postponing secrets and permissions to a later stage, and measuring success by the number of tools installed rather than by release speed and reliability.
Another mistake is choosing a provider by the length of their tool list rather than by their ability to understand your product and your team's constraints.
To avoid them, ask a few direct questions before you start working with a DevOps consultant or company:
- Who will actually do the work, and what experience do they have with an environment like yours?
- What will knowledge transfer look like, and what needs to happen for your team to manage without the provider?
- Are the recommendations tied to a platform, license or vendor the consultant earns from?
- Where will the code, configuration and documentation live, and who holds the permissions?
- What is the deliverable of the first stage, and how will you know it succeeded?
Why work with me
I came to DevOps from development. I started as an automation developer, led automation development technically in C# along with the CI/CD pipelines, and moved into DevOps roles with daily work on Kubernetes, including AKS and OpenShift, plus Terraform, Docker, Azure, Azure DevOps, GitHub and Nexus in microservices environments. Today I work as an AI Solutions Architect, building systems that have to run in production, not just in a demo, so infrastructure is part of every project I design.
I have also worked where there is no cloud and no internet access: setting up Kubernetes clusters in closed, air-gapped environments, including EKS Anywhere and OpenShift, where every component, image and update has to arrive through a controlled path.
I work independently and take no commissions from cloud or tool vendors, so recommendations are based only on what fits you. I taught as an assistant lecturer in a software engineering course at Ariel University, and the habit stuck: explain every decision so the team understands it, can change it and does not need me to keep going.
WHO YOU WORK WITH
Who works with you.
Bechor Simhaev · AI solutions architect & DevOps
I take an AI idea and turn it into a system running in your organization: RAG over your knowledge, agents and agentic workflows, and LLM-based platforms. From discovery to production.
The difference: I don’t stop at the demo. Hands-on experience in DevOps, Azure, Kubernetes and on-prem clusters in closed environments with EKS Anywhere and OpenShift means the solution is built from day one to run in your environment, with its security and permissions. And I’m independent, with no commissions and no preferred tool, so the recommendation rests only on what is right for you.
GOOD QUESTIONS
Before we start.
CI/CD for a small product: how do you build a reliable release process?Do we have to use Kubernetes?
No. Infrastructure is chosen based on the system's scale and your ability to operate it. Sometimes a managed service or a simple deployment is the better fit.
Can you improve an existing process?
Yes. We can start from one focused problem: inconsistent builds, manual deployments, scattered configuration or hard-to-diagnose failures.
Can you estimate cloud costs?
We can prepare an estimate based on the architecture and explicit load assumptions. Prices and assumptions are checked during planning and updated against real usage.
What drives the cost of a DevOps project?
Mostly scope: the number of services and environments, the starting point, security requirements, and whether you need design only or full implementation. The depth of knowledge transfer matters too. After the assessment, scope and deliverables can be defined precisely and priced accordingly.
How long does a CI/CD setup take?
A focused pipeline for one service is usually a short project, while a cloud migration or a Kubernetes rollout for a whole system takes longer. The difference comes from the number of components, the dependencies and how available your team is. A realistic timeline is set after the assessment, with milestones you can verify.
How are secrets and keys handled during the work?
Secrets never go into code or the repository. They are stored in a dedicated service such as Azure Key Vault or in the CI system's secret store, and pipelines get only the permissions they need. Part of the work is also finding secrets that already leaked into code and rotating them.
Do you need full access to our cloud account?
No. Read access is usually enough for the assessment, and during implementation permissions are scoped to the task. Access is granted through your own users and tools, and can be revoked when the work ends.
Which environments do you have experience with?
Hands-on experience with Azure, including managed Kubernetes (AKS), and with on-premises environments: setting up Kubernetes clusters in closed, air-gapped networks, including EKS Anywhere and OpenShift. CI/CD, containers and infrastructure as code follow the same principles across environments, and if your project relies on a platform I have no hands-on experience with, I will say so upfront.
Is Terraform the only option for infrastructure as code?
No. Terraform is widely used and fits many cases, but if you already have another tool that works, replacing it is not always worth it. The choice depends on what your team knows, your cloud provider and what exists today.
Can we start with a small project?
Yes, and it is usually the right way. Start with one painful problem, such as manual deployments or an unstable build, solve it fully and check the result. From there it is easier to decide whether to expand.
Does DevOps make sense for an early-stage startup?
Yes, at a scale that fits the stage. For an early startup that means a simple pipeline, separated environments and proper secrets handling, not a full platform. A small investment now saves a lot of work as the product and team grow.
How does our team learn to operate what gets built?
Knowledge transfer is part of the work, not an appendix at the end. Your team takes part in the implementation, gets runbooks and diagrams, and runs releases and incident drills themselves while I am alongside. The goal is for the team to continue on its own.
How do we know the DevOps investment paid off?
Compare baseline metrics with the state after the change: release frequency, lead time, failed releases and time to restore. It is also worth tracking how much developer time goes into infrastructure issues and how much depends on one person. That is why metrics are defined at the start of the project.
Can you work in an isolated environment without internet access?
Yes, but it shapes the design. You need an internal registry, such as Nexus, mirrors for dependencies and a controlled process for bringing in updates. These constraints are defined during the assessment so they do not surprise anyone mid-implementation.
What happens after the project ends?
The code, configuration and documentation stay with you, and your team knows how to run them. If needed, focused follow-up support can be agreed, such as a periodic review or help with the next stage, but the system should not depend on me.
LET’S MAKE IT REAL
Let’s find the right step for you.
Have an idea, a need or a question that hasn’t settled yet? Let’s work out together what’s right to do.
Let’s talk A direct conversation. A clear direction. A step that fits you.