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Tag: IT infrastructure

AWS AI Agent Surfaces Recommendations to Optimize Cloud Computing Environments

Amazon Web Services (AWS) today made available a preview of an artificial intelligence (AI) agent that surfaces recommendations to optimize cost, security, performance and resilience based on the business objectives an organization defines.

Jill Fariss, vice president of AWS Support, said the AWS Well-Architected Agent generates code that can be implemented via a command line interface (CLI), an infrastructure-as-code tool or some type of runbook automation.

The overall goal is not to eliminate the need for humans to manage IT infrastructure but rather make it simpler for engineers and IT administrators to manage workloads at much higher levels of scale, added Fariss. That capability is critical because most organizations today simply don’t have enough IT staff to effectively manage and optimize the workloads they currently have deployed, an issue that is only going to be further exacerbated as advances in AI make it possible to build and deploy even more applications, she noted.

The AWS Well-Architected Agent is designed to function much like a cloud architect that continuously correlates metrics, resource configurations, and application topology that are then analyzed using a set of best practices that AWS has defined across more than 65 of its services. Based on the goals an organization might have, it will then surface recommendations that highlight the tradeoffs that might need to be made to achieve one goal versus another, said Fariss.

In addition to presenting those consolidated findings, the AWS Well-Architected Agent also provides step-by-step remediation guidance and, when applicable, the costs that might be incurred. DevOps engineers or an IT administrator can define the business goals they are trying to meet or, alternatively, opt to run AWS Well-Architected Agent simply to discover issues and suggestions for resolving them.

It’s not clear what the future will hold for DevOps engineers and IT administrators in the AI era, but the only thing that is certain is the level of expertise required to manage complex IT environments will continue to steadily decline. In some cases, organizations will opt to rely on smaller teams of engineers to manage workloads at much higher levels of scale. In other cases, organizations may opt to augment IT administrators that typically cost less to hire and retain.

Regardless of approach, each organization will ultimately need to determine the scope of the tasks that it is comfortable with an AI agent automating with little to no intervention on the part of an IT professional necessarily being required. For now, however, AI agents that are deployed to optimize IT operations still need to establish a level of trust, said Fariss.

IT teams, ultimately, should expect the number of AI agents being made available by providers of IT infrastructure to only increase in both number and capabilities. The challenge and the opportunity then becomes determining precisely where the separation of duties and responsibilities between various AI agents and the humans that supervise them is going to lie not just today but, more importantly, a few short months from now as the capabilities of AI agents continue to expand and evolve.

October 1, 2026
SUSE Extends AI Agent Reach via MCP Server Integration

SUSE today revealed it is collaborating with multiple providers of artificial intelligence (AI) agents with the ability to manage IT infrastructure resources via integrations with the Model Context Protocol (MCP) server embedded in its platforms.

Announced at the SUSECON 2026 conference, AI agents from Fsas Technologies, n8n and Revenium, Stacklock and Amazon Web Services (AWS) can invoke the MCP server that SUSE has embedded in its Rancher Prime and SUSE Multi-Linux Manager offerings.

Rick Spencer, general manager, engineering at SUSE, said that capability makes it possible, for example, for the Amazon Quick AI agent that AWS developed to automate workflows for managing IT infrastructure resources such as Linux servers and Kubernetes clusters.

Ultimately, any AI agent that can access the SUSE MCP server should be able to, for example, identify system faults in Kubernetes clusters or Linux servers, correlate system logs, and submit a pull request (PR) or a patch to restart a service or apply updates.

The goal is to provide a secure way for AI agents to monitor, troubleshoot and optimize infrastructure across any distribution of Linux or Kubernetes using SUSE Multi-Linux Manager or the Rancher Prime management platform, said Spencer. Included in the MCP servers developed by SUSE are a set of AI engineering skills that make it possible to manage Linux servers and Kubernetes clusters, he added.

Mitch Ashley, vice president and practice lead for software lifecycle engineering at the Futurum Group, said infrastructure platforms are evolving into agent-accessible substrates. Platform evaluations must now weigh MCP surface depth alongside management features because every action exposed through MCP becomes a potential autonomous change made to a production environment, he added.

The degree to which organizations will enable AI agents to manage IT infrastructure will naturally vary by use case but it’s clear that with the advent of MCP, not every platform is going to require its own dedicated AI agent. In some instances, an AI agent developed by a third-party will simply invoke MCP to automate a task. In other instances, however, an AI agent might communicate with another AI agent that has been specifically trained to perform IT infrastructure tasks.

Regardless of approach, the days when IT teams relied on graphical tools to manage IT environments are coming to an end, said Spencer. Instead, IT teams will use natural language interfaces to instruct AI agents to perform specific tasks, he added.

In the meantime, MCP itself remains a work in progress. The next iteration of MCP will enable IT teams to deploy stateless servers that will make it easier to deploy AI tools and applications at higher levels of scale. The technical oversight committee for MCP, now being advanced under the auspices of the Agentic AI Foundation (AAIF), is also working on a task capability that will make it easier to run long-running autonomous workflows versus continuing to rely on a request and response mechanism that would otherwise need to be re-invoked multiple times.

Additionally, maintainers of the MCP project are working on adding a triggers capability that will enable servers to initiate an action, rather than always having to rely on an MCP client. Support for retry semantics, expiration policies, native streaming and reusable skills that are based on domain knowledge are additional capabilities that are expected to be added in 2026.

Finally, updates to the Python and TypeScript software development kits (SDKs) will provide access to more efficient MCP clients and servers.

In the meantime, DevOps teams should expect the number of AI agents that can manage IT infrastructure to rapidly proliferate in the days and months ahead.

April 22, 2026
System Initiative Extends Reach of IT Infrastructure Automation Platform

System Initiative today revealed it is now extending the reach of its digital twin platform for automating the management of IT infrastructure to any cloud computing environment, including now out-of-the-box support for Microsoft Azure, Digital Ocean and Hetzner services, along with existing support for Amazon Web Services (AWS).

Nick Stinemates, vice president of business development and community for System Initiative, said the company’s namesake platform can now also discover all the application programming interfaces (APIs) being employed across any cloud service.

Armed with those capabilities, DevOps teams can now take advantage of templates to more easily redeploy workloads across those environments using visual tools that are integrated with the core System Initiative platform, he added.

Additionally, IT teams can create disaster recovery plans that span multiple cloud services, noted Stinemates.

At the core of the System Initiative platform is an IT infrastructure automation platform that creates a programmable model of an IT environment to provide an abstraction layer that enables software engineering to employ reactive code to manage IT infrastructure. In effect, it provides DevOps teams with a high-fidelity digital simulation to map the relationships between the various components of an IT environment. Instead of using infrastructure-as-code using more complex tools such as Terraform, DevOps teams can then make use of small amounts of reactive functions to configure the physical IT infrastructure that System Initiative has mapped.

System Initiative has also created a set of artificial intelligence (AI) agents to make its IT infrastructure automation platform even more accessible. Collectively, those capabilities make it possible to both visualize every live resource and relationship, including security and compliance checks and actionable suggestions to improve resiliency and performance.

It’s not clear to what degree DevOps teams are ready to rely on AI agents to manage IT infrastructure, but it’s apparent that, given the number of misconfigurations that exist, existing workflows are deeply flawed. It’s simply too easy for developers using tools such as Terraform to make a mistake. The System Initiative platform fundamentally reduces dependencies on scripts that are simply too brittle to manage IT environments at scale, said Stinemates

Of course, AI agents might also be prone to making mistakes, but there will be fewer of them, especially as those AI agents become more familiar with the specific IT environment they have been tasked to automate using the guardrails that System Initiative provides to ensure they only access relevant data, noted Stinemates.

No matter how IT infrastructure is provisioned, there will always be a requirement for it to be reviewed by a DevOps engineer, he added. The challenge and the opportunity now is to automate the management of IT infrastructure at a level of scale that doesn’t necessarily require a small army of DevOps engineers to build, maintain and document thousands of scripts.

In the meantime, however, DevOps teams would be well-advised to re-evaluate how existing workflows are managed with an eye toward streamlining as many existing processes as possible as the number of workloads that are deployed start to exponentially increase.

November 18, 2025
AWS to Help Fund Open VSX Registry Hosted by Eclipse Foundation

The Eclipse Foundation this week revealed that Amazon Web Services (AWS) is providing funds needed to strengthen the reliability, performance and security of the infrastructure used to make the Open VSX Registry, an online marketplace for Visual Studio Code extensions.

Like other AI coding tools, the Kiro tool developed by AWS relies heavily on Visual Studio Code extensions that the Eclipse Foundation makes available under an open source license.

Mike Milinkovich, executive director of the Eclipse Foundation, said that as these tools have become used more widely, the stress on the underlying infrastructure used to host Open VSX Registry has significantly increased. The registry now hosts more than 7,000 extensions from nearly 5,000 publishers, with downloads exceeding more than 110 million per month but is only supported by three engineers.

The Eclipse Foundation has not agreed to migrate Open VSX Registry to the AWS cloud in return for this investment, but might as part of an effort to reduce costs. AWS, however, is providing infrastructure and services that will improve availability, performance and scalability across the systems currently used to host the registry, along with future initiatives planned by the Eclipse Foundation.

Nor is the AWS investment a direct result of an open letter that several open source foundations recently published concerning the economic viability of providing services such as Open VSX Registry, the need for additional sources of funding remains, said Milinkovich.

At the core of the issue is the simple fact that the vendors and non-profit entities that originally launched and support open source projects that are consumed as a service are shouldering the cost of maintaining the underlying IT infrastructure required with no way to recoup that investment. The overwhelming majority of large-scale users, including commercial entities that extract economic value, consume these services without contributing to their financial sustainability.

Rectifying the economic imbalance is going to require commercial and institutional partnerships that help fund infrastructure in ways that are aligned to usage and/or adoption of tiered access models through which fees might be levied on organizations that consume large amounts of IT infrastructure resources.

The open letter is the first step toward raising awareness of an issue that will eventually need to be addressed, for example, by throttling and rate limiting to moderate usage of package managers that were never supposed to become critical elements of a software development process. The hope is that individual developers that rely on those services will become more judicious about how they are incorporated into software development workflows.

It’s not precisely clear how much is being spent on IT infrastructure to support these projects but costs are in the tens of millions with no sign of abatement. In effect, open source projects are becoming economic victims of their own success. The issue now is determining how best to fund these projects in a way that is more sustainable with the aid of more financial resources that will, hopefully, soon be more forthcoming.

November 6, 2025
The Integration Trap: When Your “Seamless” System Crashes at the Worst Possible Moment
Imagine this: You have just finished implementing a big, enterprise-level software. The project took months (or years), cost a fortune and required countless hours of work. But you did it! Now, it is finally time to reap the ROI from your investment. But guess what? You also have to deal with the consequences.

Integration: A Dream Come True or a Never-Ending Nightmare?

Your shiny new innovative system doesn’t exist in isolation. It needs to communicate with other systems. And how is that done? Through integrations.

In the past, this meant a more tedious process with file transfers, spreadsheets and manual workarounds. Today, it is all about application programming interfaces (APIs) and middleware, connecting:
- ERP ↔ Supply Chain System
- ERP ↔ Inventory System
- ERP ↔ Accounts payable (AP) Automation
- ERP ↔ Vendor Systems and so on
Each connection is a delicate web of API calls, middleware and message queues — basically, a high-stakes effort of digital matchmaking between two systems that were never really meant to talk to each other. One system speaks French, the other grunts in a Greek dialect and middleware is the overworked translator trying to facilitate seamless communication without chaos.

And these aren’t small, one-off data syncs. We are talking about thousands of transactions per day — millions per month. The more users, the more operations, the more data flying back and forth, trying to keep everything running smoothly or spiraling into chaos.

The Integration Party: Where Wine Meets Emergency Support

Let me tell you a fun story about a real project.

After two years of hard work, hundreds of hours of meetings — both virtual and in-person — brainstorming, arguing, implementing and coding, we finally rolled out a brand-new enterprise resource planning (ERP) system to replace an old, custom-built dinosaur.

But instead of fully switching to the ERP’s inventory system, the company decided to stick to its old inventory software. They were promised seamless integration. And, frankly, they couldn’t live without it. They had too many custom processes they thought were too important to lose.

“It will be easy!” said the partners. “Flawless data flow!” they assured. “API technology is a universal language for all systems.”

Well… not exactly.

The two systems operated in completely different ways, especially when it came to handling inventory transactions. And that’s where the IT technical teams came in — to bridge the gap, untangle the mess and make it work anyway.

Trying to streamline transactions, handle exceptions and manage special cases became the new daily grind.

The Go-Live

Fast forward to go-live — everything seemed almost perfect.

No major issues, no fires and no 2 a.m. crisis calls. Additionally, let me tell you there is no such thing as ‘no issues’ in any project. Nevertheless, much to our surprise, this project only had minor issues.

The CEO decided to throw a dinner party in honor of our success for all the teams that had contributed to the project.

And then, it happened.

While we were at the party, one of the main connection agents — the glue between the ERP and inventory system — crashed. Suddenly, no more transactions were passing through.

Orders? Stuck.

Shipments? Frozen.

Bills of lading? Not printing.

Moreover, it was nearing the end of the second shift and people wanted to go home after a long working day. So, some of them ended their shift a bit early to avoid the hassle of staying around and troubleshooting.

Phones started ringing. Emails and texts started flooding in. Panic set in.

Then came the real kicker: The managed services team did not have access to troubleshoot the integration agent. Only the technical team could fix it.

And where was the technical team? At the party. Drinking wine. Lots of it.

So now, a group of half-drunk engineers had to jump on a call and troubleshoot a mission-critical integration failure.

You can imagine how well that went.

By the time the issue was resolved, the damage was already done. Thousands of failed transactions had to be manually corrected, inventory mismatches had to be reconciled and most importantly, we learned a valuable lesson: A ‘seamless’ integration is only seamless until it is not.

Key Takeaway: Integrations Can be Problematic

Modern API-based integrations are reliable, efficient and faster than ever. The technology has evolved, proving itself across countless organizations with real-world success stories.

Let us not forget the brilliant technical minds who, with the right direction, motivation and management, can navigate the complex puzzles of integration and make even the messiest systems talk to each other.

But here is the question: Just because two systems can be integrated, does that mean they should? Is that integration truly needed or is it just an ambition of a long-term system strategy?

As an IT person, this type of project works in my favor, so perhaps I shouldn’t talk about it. But the truth is, integration projects can be risky. The more transactions and transaction types you integrate, the more risk you introduce into the equation. The more different the systems are, the more chaos can unfold. Issues will keep surfacing like a contagious sneeze in a crowded room.

This means that before choosing a product, organizations need to consider how the systems can actually work together.

How Different Can They Really Be?

A common argument: ‘How different can they be? Every system is just capturing transactions, right?

Wrong. Every system has its own design, structure and logic — and sometimes, those do not just differ; they conflict.

For example, one system batch processes transactions, while the other requires real-time sync.

Different database structures: One requires unique item IDs, while the other happily allows duplicates. One specific transaction type is designed with header/detail logic, while the other only stores details.

And what is the result?
- Data conflicts
- Lost transactions
- A giant, expensive mess to untangle
Sure, a strong technical team can work through these puzzles, but at what cost?

More Dependencies = More Vulnerabilities

The more dependencies you create, the more fragile your ecosystem becomes, especially when you are working with a brand-new product that your team has no internal knowledge of.

Suddenly, you do not just need a general IT team — you need integration specialists. People who do not just know how to connect systems, but also how to debug, troubleshoot and untangle them when they inevitably fail.

Have a Plan B for When Integrations Fail

This is what we call business continuity. When your integrations fail (because they will), do you:
- Have a backup process that allows transactions to keep flowing?
- Have an emergency troubleshooting team available 24/7?
- Have proper logging and alerts to catch failures before they spiral out of control?
If your entire business grinds to a halt just because one API call fails, then guess what? You do not have an integration. You have a single point of failure disguised as a solution.

Final Thought: Invest in What You Need, Not What Looks Good

Organizations need to invest in the software they need, not just what looks innovative and exciting on paper. A well-chosen system with fewer dependencies will always bring better ROI than a ‘groundbreaking’ solution that relies on layers of fragile integrations.

There must be a thorough and proper internal evaluation of the basic requirements of the new software. At the end of the day, it is not about how modern or feature-rich a product is, it is about how well it works for the business.

The next time your client says, ‘Don’t worry, the integration will be seamless’, ask yourself: ‘How many drunk engineers will it take to fix it at 10 p.m. at a party on a Saturday’?

That is the real ROI calculation.
May 13, 2025
Spacelift Applies Generative AI to Infrastructure Automation

Spacelift, this week, added generative artificial intelligence (AI) capabilities to its platform for automating the management of IT infrastructure provisioned using code.

Company CEO Pawel Hytry said Saturnhead AI adds a set of AI capabilities that can, for example, be used to identify issues and suggest potential remediations to make it easier for DevOps teams to troubleshoot complex IT infrastructure environments.

Compatible with multiple large language models (LLMs) that DevOps teams can specify, Saturnhead AI is able to analyze infrastructure logs in real time to explain in natural language what has happened and why it occurred. That capability eliminates the need to otherwise manually sift through those infrastructure logs in IT environments where there might be thousands of failed runs per week, noted Hytry.

While many DevOps teams routinely make use of infrastructure-as-code (IaC) tools, managing IT infrastructure remains challenging. A recent Spacelift survey found that only 14% of respondents have fully implemented infrastructure automation best practices. Generative AI tools have the potential to enable more organizations to more consistently apply best DevOps practices in an era where IT infrastructure has become too complex for humans to manage, noted Hytry.

Less clear is the degree to which AI might enable junior members of a DevOps team to effectively manage IT infrastructure at scale versus allowing senior members of a DevOps team to manage IT infrastructure at much higher levels of scale. The one certain thing is that it will become easier for DevOps teams to share tribal knowledge about how infrastructure is configured, said Hytry.

Each organization will need to determine how best to apply AI to managing IT infrastructure, but there will always be a need for humans to supervise AI models, said Hytry.

Spacelift, while still investigating the potential role AI agents might play in automating the management of IT infrastructure, is pursuing a more conservative approach given the number of errors that might be injected into a DevOps workflow, said Hytry. Most IT operations teams are going to be reluctant to rely on any form of automation that might inadvertently make critical IT infrastructure suddenly unavailable to applications, he added.

A recent Futurum Research survey finds 41% of respondents expect generative AI tools and platforms will be used to generate, review and test code, but the degree to which AI will be relied on to manage IT infrastructure is a little less clear. The one certain thing is that IT infrastructure is only going to become more challenging than ever to manage. Unfortunately, many of the processes being employed by application developers are far more manual than they should be, which creates more opportunities for misconfigurations. As a result, application developers are spending time on a set of tasks that, in addition to possibly introducing cybersecurity risks, also take time away from writing code.

Hopefully, advances in artificial intelligence (AI) will soon make it easier to discover and remediate these issues faster. In the meantime, however, DevOps teams would be well advised to invest more in automation to ensure infrastructure is not only being provisioned faster but also more reliably.

April 18, 2025
How to Keep Your IT Infrastructure Invisible

IT infrastructure is critical. IT infrastructure enables businesses to run—from day-to-day operational execution to visionary strategic innovation and everything in between. What’s interesting, though, is that people are only aware of it when there’s a problem: HR can’t access the payroll application, customers are complaining about how slow the transactional system is or this month’s cloud bill was double what you expected it to be.

No one should notice a well-orchestrated environment, but once application performance slows or an outage occurs, people start to grumble. The same is true for IT infrastructure.

The Top Four Ways Your IT Infrastructure Can Become Undesirably Visible

Given the complexity of modern hybrid/multi-cloud environments and the applications they support, it’s no surprise that countless things can go wrong—and when they do, your IT team takes the flack.

If your infrastructure is humming along nicely, that’s a testament to the IT infrastructure team’s hard work and expertise. Sadly, they don’t get the recognition because it’s all invisible to the rest of the organization. It’s only when *BAM!* something happens that the team is scrutinized.

While there are many ways this can manifest, it usually falls under one of the following four categories:

• Availability — This may be the most catastrophic because when systems are unavailable, people can’t do whatever it is they need to do.
• Performance — A system might be available, but that doesn’t mean it’s performing to SLA or user expectations. The result can range from minor annoyance to lost revenue and customer churn.
• Cost — Runaway expenditures don’t necessarily affect users, but you do not want to be called to account by the finance team or, worse, executive leadership.
• Compliance — This is another area that may not have a broad impact on user experience, but the repercussions of non-compliance can be financially and reputationally significant.

Common Infrastructure Culprits and How to Address Them

To ensure the necessary availability, performance, cost control and compliance to keep your IT infrastructure under the radar, you must understand what can cause problems in these areas. Here are eight common culprits, along with ways you can address them, so your IT team stays invisible.

Broken or Misunderstood Dependencies
Your infrastructure is a complex web of interdependent applications and services. Every time you make a change, it could have a rippling effect on the categories mentioned above. Automated discovery and service mapping capabilities enable you to easily trace dependencies throughout your infrastructure to avoid unintended consequences.

Cloud Waste
Chances are very high that you’ve got cloud waste. This means that you could be getting billed for a storage block that’s attached to a stopped instance, for compute instances that are not being used, or for unattached load balancers. Finding idle and abandoned resources can keep your monthly cloud bill under control and on budget.

Un-Breakdownable Cloud Costs
Cloud bills are notoriously complex, and while cloud providers do offer tools to help you analyze your cloud spend, those tools often don’t answer all the questions your business might have. In addition to adding clarity to such opaque expenses, you need to be able to parse your cloud spend based on what makes business sense to your organization, not what makes technical sense to your cloud provider.

Poor Capacity Planning
Your infrastructure needs to meet your business needs, which are continuously evolving. As changes happen, whether it’s increased utilization of existing resources or modified/added resources to support new requirements, workloads could push current capacity and impact performance and stability. You need to be able to forecast infrastructure demands against business objectives to minimize potential issues before they happen.

Poor Workload Placement Decisions
Your infrastructure consists of various environments each with its own characteristics. If you migrate a workload without understanding the implications of that particular environment, you could risk performance problems or spiking costs. To prevent this, you need any-to-any migration insights to make better decisions about workload priorities, groups and deployments.

Poor Reservation Planning
Reservations (i.e., reserved instances or programmatic discounts) offer discounts for committing to a particular plan. If you plan well, the savings can be significant. But if you don’t use the capacity you’ve bought, the savings might not materialize. To improve cloud resource planning, you need to be able to evaluate your potential savings in varied scenarios.

Workload Drift
Over time, your workloads evolve due to changing demand, data volumes, etc. As a result, they can outgrow their current configurations, leading to performance issues or rising costs. This is a natural result of business growth, so the goal isn’t to prevent that drift. Instead, you want to optimize capacity and cost on an ongoing basis to keep your workloads right-sized.

Slow Problem Troubleshooting and Remediation
No matter how many precautions you take, something somewhere will inevitably go wrong. And once you become aware of the situation, the clock starts ticking to find the cause and fix it, all of which takes time. The longer the entire process takes, the longer your infrastructure will be visibly and painfully not working as expected. For those cases, you need full-stack visibility with application-centric, AI-based analytics to minimize impact duration as much as possible.

Keeping the engine running behind the curtain can be a daunting task, but with proper planning and management, your IT team will remain visible to those responsible for managing it and invisible to those in the rest of the organization. Of course, the complexity of today’s cloud infrastructure makes that challenging, and there will be IT fire drills that take place, but it’s about how IT leaders react to the situation and resolve it in the quickest way possible, allowing themselves to return to their preferred place in the shadows.

July 7, 2023
Cloud Orchestration and its Impact on DevOps Teams
Cloud orchestration refers to the coordination and management of various interconnected cloud services and resources to automate and streamline complex IT processes. In simple terms, it is the process of integrating, synchronizing, and automating various cloud-based components to create a seamless and unified workflow.

Cloud orchestration aims to optimize the deployment, management, and use of resources in a cloud environment, improving efficiency, reducing costs, and ensuring that cloud services are delivered in a timely and effective manner. It is related to the concept of CloudOps (cloud operations), which uses cloud orchestration concepts to allow more efficient management of cloud resources. Cloud orchestration is a critical aspect of modern IT infrastructure management, as it enables organizations to manage and control their cloud resources more effectively.

Difference between Cloud Orchestration and Cloud Automation

Though the terms cloud orchestration and cloud automation are often used interchangeably, they have distinct differences.

Cloud automation refers to the process of automating individual tasks and processes within the cloud environment. It involves the use of scripts, templates and other tools to automate repetitive tasks, such as provisioning resources, deploying applications and configuring environments. The primary goal of cloud automation is to reduce the time and effort needed to manage cloud resources.

Cloud orchestration is a broader concept that encompasses not only the automation of tasks but also the coordination and management of the entire cloud ecosystem. It involves the integration of various cloud services, tools and resources to create a unified, streamlined workflow. Cloud orchestration ensures that all components in the cloud environment work together seamlessly, automating complex processes and managing dependencies between tasks.

In essence, cloud automation is a subset of cloud orchestration. While cloud automation focuses on automating individual tasks, cloud orchestration takes a more holistic approach, orchestrating multiple tasks and resources to achieve a higher level of automation and efficiency.

How Cloud Orchestration Enhances DevOps Practices

Increased Efficiency and Speed

One of the main benefits of cloud orchestration in a DevOps context is the ability to increase efficiency and speed in the software development and deployment process. By automating and streamlining various tasks, cloud orchestration eliminates manual processes, reduces the potential for human error and accelerates the overall development cycle.

Improved Collaboration and Communication

Cloud orchestration fosters better collaboration and communication between development and operations teams by providing a unified platform for managing cloud resources. This shared platform enables teams to work together more effectively, breaking down traditional silos and ensuring that all stakeholders have visibility into the development and deployment process.

Enhanced Infrastructure and Application Management

Cloud orchestration simplifies the management of complex cloud infrastructure by providing a single, unified platform for cloud optimization—improving the management of resources, applications and services in the cloud.

This centralized management approach enables organizations to more easily monitor, control and optimize their cloud environment, ensuring that resources are used effectively and that applications are running smoothly. With cloud orchestration, organizations can more easily scale their infrastructure to meet changing demands, ensuring that they have the resources they need when they need them.

Improved Monitoring and Troubleshooting

Cloud orchestration provides improved monitoring and troubleshooting capabilities, enabling organizations to more effectively identify and address issues in their cloud environment. With comprehensive monitoring tools and dashboards, teams can gain insight into the performance of their applications, identify bottlenecks and pinpoint potential issues before they become critical.

Challenges of Integrating Cloud Orchestration With DevOps

Despite the numerous benefits of cloud orchestration, integrating it into DevOps practices can present several challenges. Some of the common challenges include:
- Complexity: Cloud orchestration involves the integration of various cloud services, tools and resources, which can be complex and time-consuming. Organizations may struggle with complexity, particularly if they lack the necessary expertise or resources to effectively implement and manage the solution.
- Resistance to change: Implementing cloud orchestration requires a change in mindset and approach to software development and deployment. As your organization migrates more systems to the cloud, some team members may be resistant to adopting new processes and tools, making it difficult to fully embrace and realize the benefits of cloud orchestration.
- Security concerns: As with any cloud-based solution, security is a critical concern when integrating cloud orchestration into DevOps practices. Organizations must ensure that their solution is secure and that they have the necessary policies and procedures in place to protect their sensitive data and resources.
- Cost and resource constraints: Implementing and managing a Cloud Orchestration solution can be resource-intensive, requiring significant investment in infrastructure, tools, and personnel. Organizations must carefully consider the costs and resources required to implement cloud orchestration and determine whether the benefits outweigh the investment.
Best Practices to Integrate Cloud Orchestration Into DevOps

To successfully integrate cloud orchestration into DevOps practices and overcome the challenges mentioned above, organizations should consider the following best practices:
- Assess your organization’s readiness: Before implementation, evaluate your organization’s readiness for change. This includes assessing your existing infrastructure, processes and tools, as well as your team’s willingness and ability to adopt new practices and technologies.
- Develop a clear strategy: Develop a clear strategy for integrating cloud orchestration into your DevOps practices. This should include defining your goals and objectives, identifying the tools and resources you will need and establishing a timeline for implementation.
- Choose the right tools and technologies: Select the appropriate tools and technologies that best meet your organization’s needs and requirements. Consider factors such as ease of integration, scalability, security and cost when evaluating potential solutions.
- Train and educate your team: Ensure that your team has the necessary knowledge and skills to effectively implement and manage cloud orchestration. This may involve providing training and education on new tools, processes and best practices, as well as fostering a culture of continuous learning and improvement.
- Monitor and measure success: Continuously monitor and measure the success of your implementation. This includes tracking key performance indicators (KPIs), such as deployment speed, resource utilization and application performance, to ensure that your solution is delivering the desired results.
Conclusion

Cloud orchestration is an essential tool for organizations looking to streamline and optimize their IT infrastructure, particularly in the context of DevOps practices. By automating and coordinating complex cloud processes, organizations can improve efficiency, speed, collaboration and overall performance.

However, successfully integrating with DevOps can be challenging, requiring a clear strategy, the right tools and technologies and a commitment to continuous improvement. By following the best practices outlined in this guide, organizations can overcome these challenges and fully realize the benefits.
July 6, 2023
Fiberplane Notebook Tool Fosters DevOps Collaboration

Fiberplane today announced it is making available a public beta of a namesake real-time collaboration notebook specifically designed for DevOps teams that need to quickly debug IT infrastructure.

Fiberplane CEO Micha Hernandez van Leuffen said in the wake of the COVID-19 pandemic, it’s clear that the structure of DevOps teams has permanently changed now that more members of those teams work remotely. The challenge is that the tools provided to DevOps teams to manage IT environments were not designed to foster the level of collaboration that is now required, he added.

Dashboards that were designed in a different era need to be replaced with tools that make it simpler for DevOps teams to collaboratively debug infrastructure in real-time, noted Hernandez van Leuffen.

The Fiberplane notebook achieves that goal by using the same operational transformation algorithm used in Google Docs to enable teams to easily collaborate around a document or spreadsheet. The core platform itself is built in Rust and WebAssembly (Wasm), which Hernandez van Leuffen said makes it simpler to integrate Fiberplane as a plug-in into an existing DevOps workflow. Inside a Fiberplane Notebook, DevOps teams can, for example, write and run PromQL queries and display Prometheus charts alongside other data presented via an integrated graph.

Fiberplane Notebook’s initial integrations are for Grafana Loki, Elasticsearch and Prometheus monitoring tools. It also exposes both an application programming interface (API) and command line interface (CLI) to automate notebook creation based on specific external events, such as monitoring alerts.

In effect, Fiberplane is taking the concept of notebooks used for collaboration by data science teams and applying it to DevOps workflows, said Hernandez van Leuffen. The goal is to improve DevOps teams’ productivity by reducing the amount of time it takes to resolve any issue, he added.

As IT environments become more distributed in the age of the cloud and microservices, troubleshooting issues invariably spans the responsibilities of multiple members of an IT team. Fiberplane, in effect, makes it possible to spin up a virtual war room that enables the members of an IT organization to collaborate until the issue of the moment is resolved.

The speed at which any IT issue is resolved has become a crucial metric. Given the complexity of IT environments, it’s inevitable that incidents will arise. Ideally, IT teams would discover those issues before they disrupt the business. However, in reality, the metrics organizations use to evaluate the effectiveness of a DevOps team are, unfairly or not, how quickly IT issues are resolved once they are discovered. The longer it takes for a distributed DevOps team to marshal its resources the more likely it becomes that team will be perceived as being inefficient—regardless of what level of application availability is actually achieved.

Savvy DevOps teams, of course, have implemented a wide range of incident management best practices that create a level of muscle memory for responding to a wide range of issues. The trouble is there will always be unforeseen issues that arise. DevOps teams, as a result, need to find ways to quickly focus on an issue that, for one reason or another, were simply too unpredictable to anticipate; they need to expect the unexpected.

November 15, 2022
Change and Order

July 9, 2021