devopsy.kinsta.cloud

Tag: budget

App Migration: How to Build a Winning Risk Management Plan
While offering many tangible benefits, application migration — the process of transferring a software solution from one computing environment to another — is always associated with certain risks. Data loss, budget overruns and security vulnerabilities are just a few examples of issues that can arise during your app migration journey, compromising overall project success.

To ensure a smooth app migration and secure your project’s ROI, your company must identify these and other risks early on, define a risk mitigation strategy, and follow it throughout the project. In other words, you should prepare and implement a risk management plan for app migration.

In this article, experts from Itransition, a company that provides app migration services, highlight the common risks associated with app migration and specify steps for building an efficient risk management plan.

What are the Most Common Application Migration Risks?

Application migration risks can vary from case to case, depending on various factors, such as the scope and complexity of the app migration. But from our experience, the following types of risks are among the most commonly encountered ones:
- Data loss
Due to various reasons (human error, data incompatibility, etc.), some corporate data can be corrupted or lost during the migration process, which can lead to operational disruptions, reputational damage, legal fees and other concerns for an organization.
- Unplanned downtime
Migration projects also entail the risk of technical failures, from software bugs to database crashes, which can compromise the performance of the migrated solution and cause downtime, resulting in operational and service disruptions.
- Budget overrun
Inaccurate migration scoping and inadequate planning can lead to unplanned expenses and significant budget overruns, which in turn can reduce the overall project ROI.
- Security vulnerabilities
If the migration team fails to address potential security vulnerabilities in the transferred application or its underlying infrastructure, an organization can become a victim of cybercriminals aiming to intercept and steal its data.

Risk Management Planning: Key Steps

To create a well-rounded and efficient plan supporting your app migration, an organization can follow this four-step algorithm:
1. Identify the Most Probable Risks That Could Impact App Migration
As stated earlier, all app migration projects are unique, so to understand which risks pose the greatest threat in your unique business case, you should conduct some preliminary work, starting with the analysis of your overall migration context.

Specifically, you should carefully audit all digital assets you plan to migrate, as well as those that will be affected by the migration, including applications, databases and software integrations. You should carefully document all of these assets, as well as the dependencies that exist between them within your IT infrastructure. It is also important to carefully examine apps planned for migration in terms of their performance, security, and compatibility with the target environment.

Once you have collected and studied all this information, you can utilize various risk identification techniques to understand what potential migration pitfalls may arise. You can start by holding brainstorming sessions with your stakeholders (IT teams, business leaders, compliance officers, etc.) to find out what they think about potential risks and their probability.

It’s also key to review checklists addressing the risks common to your industry and business niche to assess their likelihood as well as learn from the experience of other organizations. Also, if your company has previously undertaken a similar migration project that encountered budget overruns, data loss, or other issues, you can investigate their root causes to understand how to avoid them in your upcoming initiative.
1. Assess and Prioritize the Identified App Migration Risks
Once you have compiled a list of the most likely risks, examine each one to determine which of them pose the greatest threat and what impact they might have on your application, business processes, and organization as a whole. To perform an efficient risk analysis, you can use such a well-known technique such as a risk assessment matrix.

The simplest way to use the matrix is to build a two-axis chart, with the horizontal axis representing the likelihood of a risk (ranging from “high” to “low”) and the vertical axis representing the potential danger or impact of a risk (ranging from “negligible” to “crucial”). By distributing risks on this chart, you can prioritize risks and define which ones require the most attention. This will help you choose the right risk mitigation strategies in the future.
1. Define the Right Risk Management Strategy for Your Migration Project
Once you have identified the risks and determined which ones to focus your mitigation efforts on, you should decide which strategies and tactics to include in your plan to effectively manage your unique challenges. For example, if there is a high risk of unplanned downtime, you should include a disaster recovery strategy in your plan to minimize the potential harm. If you risk facing a budget overrun, make sure your project budget includes contingency reserves to cover any unexpected expenses.

Regardless of which risks you consider most critical, it is essential to incorporate general risk management best practices into your plan. These can include backing up and encrypting all sensitive data before the migration, using continuous monitoring tools to detect emerging types of security threats, and implementing a change management strategy to ensure user adoption after the migration and minimize potential disruptions to your operations.
1. Continuously Adjust Your Plan Even After the Migration Starts
Once your migration project begins, you should continually evaluate risks and the effectiveness of your risk management plan. Track key metrics such as the number of risks that occurred, the number of risks mitigated and the average time to resolve a risk to understand how adequate and reliable your plan is.

In case you refine your plan by incorporating additional risk mitigation tactics, communicate all substantial plan updates to the parties involved in the project to ensure that everyone remains on the same page.

Final Thoughts

Application migration comes with numerous risks, and you should be prepared to mitigate them to ensure a smooth and successful app transfer. Data loss, security vulnerabilities, budget overruns and unplanned downtime are some common pitfalls an organization risks facing throughout the migration journey. Nonetheless, you can mitigate these risks by implementing a robust risk management plan, and the brief guide provided in this article can help you develop one.

Navigating migration risks can be too daunting, especially if your organization has not previously been involved in app migration projects. In this case, it is advisable to contact third-party app migration experts. They will analyze the apps you are going to migrate, identify the most probable risks and provide a tailored risk management plan to guide you throughout the project, helping to secure your technology ROI.
June 27, 2025
Survey Surfaces Depth of Mainframe Application Migration Challenges

A global survey of 309 decision-makers responsible for modernizing mainframe applications finds that while 69% of respondents said the initiatives are either very or extremely important for enabling their organizations to achieve their business objectives, only 18% of the budget allocated for these projects is being used to specifically modernize or rewrite those applications.

Conducted by Forrester Consulting on behalf of Rocket Software, more than half of respondents (51%) report their organization has, following multiple failures, attempted at least six rewrite projects.

The survey also notes that only 17% are focused on transforming applications on the mainframe by implementing and exploiting the most modern features available on the platform.

Just over a quarter (27%), however, are removing applications from the mainframe in favor of hosting them using cloud platforms and/or another distributed computing environment. Well over half (56%) are integrating mainframe applications with applications that have either moved to the cloud or were originally developed and deployed in the cloud, the survey finds.

Phil Buckellew, president of the Infrastructure Modernization Business Unit for Rocket Software, said there is more focus on integration rather than rewriting or migrating mainframe applications, simply because of their size and complexity. Many of those applications were also developed by individuals who are no longer with that organization and documentation available is often limited, he added.

Nearly three-quarters of respondents (74%) did note they are methodically planning to use AI to accelerate their modernization efforts. Additionally, 67% said their strategy includes a lot of experimentation and learning as it goes, with 66% reporting AI has already made them more efficient.

However, 35% also said ungoverned AI has led to significant loss of revenue and/or delayed initiatives.

In general, the survey finds half of respondents (50%) said mainframe modernization efforts are being led by IT teams, but 42% also said the strategy was being driven by those at the C-level in their organization. Nearly half (49%) said there is also a need for greater alignment between the business and IT.

The single biggest mainframe application modernization issue organizations encounter is, not surprisingly, security and risk concerns (41%), followed by a lack of talent/skills (38%). Additionally, 34% were challenged by complex integration strategies, while around 31% were burdened by inadequate software tools/platforms. A total of 30% also cited ungoverned use of new technology such as artificial intelligence (AI).

On the plus side, 45% are upskilling and training employees, while 41% are investing in new technologies to drive innovation. A total of 40% are also investing in various partnerships to achieve that goal.

Those partnerships are crucial because most IT organizations don’t have a lot of experience modernizing mainframe applications, noted Buckellew. Capabilities sought from partners include code and data modernization (83%), DevOps expertise (79%), open-source compliance (78%), knowledge of agile application development and low-code tools (75%), structured and unstructured data management (74%), vulnerability management (71%) and AI and automation (70%).

Modernization initiatives will differ substantially from one organization to another and it’s not precisely clear how AI might accelerate them but the one certain thing is more organizations than ever will be once again revisiting their mainframe application strategy in the months ahead.

October 4, 2024
Azure Cost Optimization: A Complete Guide

Microsoft Azure is one of the “big three” cloud providers, and is a primary part of IT expenditure for many companies. Azure cost optimization is a strategy that involves managing and controlling Azure costs to ensure efficient usage and spending. It requires a thorough understanding of where and how your resources are being used, as well as insight into the various pricing options available.

Azure cost optimization involves implementing best practices related to managing cloud costs, such as turning off resources when not in use, choosing the right-sized resources, taking advantage of Azure discounts and more. By optimizing these aspects, you can ensure that you are only paying for the resources you need and are using them efficiently.

Azure cost optimization is an ongoing strategy that involves constant monitoring and adjustments as your usage and needs evolve. This means that you need to be proactive and vigilant in your cost management efforts, regularly reviewing your usage patterns and making adjustments as necessary.

Why is Azure Cost Optimization Important?

As organizations migrate more and more of their workloads to the cloud, the costs associated with Azure usage can quickly escalate if not properly managed. This can lead to budget overruns and decreased profitability.

By leveraging Azure cost optimization strategies, businesses can gain greater control over their Azure spending. This not only helps in reducing costs but also enables businesses to more accurately predict their future cloud spending. This can be a major advantage when it comes to financial planning and budgeting.

Moreover, Azure cost optimization can also lead to improved operational efficiency. By ensuring that resources are used efficiently, businesses can avoid wasted spend and focus their resources on the tasks that truly add value to their operations. This can lead to increased productivity and better overall performance.

Azure Cost Optimization Tools

Azure provides several free tools designed to help customers optimize their cloud spending. These tools provide insights into your usage patterns, help you identify potential cost savings, and guide you in implementing best practices for cost management.

Azure Cost Management and Billing

Azure Cost Management and Billing provides detailed insights into your Azure spending. It allows you to track your spending by resource, location, service, and more, enabling you to identify where your money is going.

With Azure Cost Management and Billing, you can set up budgets to control your spending and set up alerts to notify you when you’re nearing your budget limits. You can also analyze your spending trends over time, which can be useful for forecasting future costs.

Azure Advisor

Azure Advisor provides personalized recommendations based on your usage and configurations, helping you optimize your resources for cost, performance, security and reliability.

Azure Advisor can identify unused or underutilized resources you can shut down or resize to save money. It also provides recommendations for purchasing reserved instances or using Azure Hybrid Benefit, which can lead to significant cost savings.

Azure Pricing Calculator

The Azure Pricing Calculator is a tool for estimating the cost of Azure services before you use them. You can input your expected resource usage, and the calculator will provide an estimate of the costs.

This tool can be especially useful when you’re planning a new workload or considering a migration to Azure. By understanding the potential costs upfront, you can make more informed decisions and avoid surprises.

Azure Monitor

Azure Monitor is a comprehensive service that provides insights into your application performance, infrastructure, and network. While primarily used for performance monitoring, it can also provide valuable insights for cost optimization.

For example, Azure Monitor can help you identify overutilized or underutilized resources, enabling you to make adjustments to optimize your costs. It can also help you track your resource usage over time, providing insights into your spending patterns.

Azure Resource Graph

Lastly, Azure Resource Graph is a service that enables you to explore your Azure resources at scale. It provides a unified view of your resources across all your subscriptions, making it easier to manage and optimize your resources.

With Azure Resource Graph, you can quickly identify resources that are not in use or are underutilized, allowing you to reduce unnecessary spending. It also enables you to visualize your resource usage, helping you understand your spending patterns better.

6 Strategies for Azure Cost Optimization

Now that we are familiar with the basics of cost optimization on Azure and the tools the platform provides, let’s review some strategies that can help you optimize and reduce costs in Azure.

1. Right-Sizing Azure Resources

One of the simplest yet most impactful strategies for Azure cost optimization is to right-size your Azure resources. This involves matching your business requirements with the appropriate Azure resources in terms of type, size and quantity.

Too often, organizations over-provision their Azure resources, which leads to unnecessary expenditures. By right-sizing, you ensure that you’re only paying for what you need. This can be achieved by closely monitoring your Azure resources usage, identifying any underutilized resources, and scaling them back accordingly.

Remember, Azure provides a range of resource types, each with its own set of capabilities and costs. Always cross-verify whether the selected resource is the most cost-effective one for your specific use case. For instance, if your application doesn’t require high compute power, choosing a lower-tier virtual machine could significantly reduce your costs.

2. Utilizing Azure Budgets and Alerts

Azure Budgets and Alerts are powerful tools for cost management. They provide you with the ability to set a budget for your Azure spending and receive alerts when your spending approaches or exceeds your budget.

Setting up an Azure budget is a proactive approach to cost management. It allows you to allocate your finances effectively and avoid any unexpected charges. Furthermore, with Azure alerts, you can instantly get notified when your consumption is nearing your budget. This gives you ample time to adjust your usage or increase your budget, preventing any service disruptions due to overspending.

Moreover, Azure Budgets and Alerts are highly customizable. You can create multiple budgets for different scopes (like management groups, subscriptions, or resource groups), set your alert conditions, and even automate actions based on these alerts using Azure Logic Apps.

3. Tagging and Resource Organization

Azure tagging and resource organization is another crucial strategy for Azure cost optimization. Tags are user-defined key-value pairs that you can assign to your Azure resources. They help you categorize and manage your resources based on your business needs.

By effectively tagging your Azure resources, you can gain visibility into your resource consumption at a granular level. This can help you identify any high-cost resources, track your spending by project, department or environment, and make informed decisions about cost optimization.

Organizing your resources into logical groups can also simplify management and governance. For instance, you can group your resources based on their life cycle or purpose and apply consistent policies and access controls across the group. This not only improves security and compliance but also helps in identifying any redundant resources that can be eliminated to save costs.

4. Utilizing Storage Tiers Based on Usage Requirements

Another effective strategy for Azure cost optimization is to utilize different storage tiers based on your usage requirements. Azure Storage provides three access tiers – hot, cool and archive, each designed for different types of data.

The Hot tier is for data that is frequently accessed and requires low latency. It has higher storage costs but lower access costs. The Cool tier is for infrequently accessed data, offering lower storage costs but higher access costs. Finally, the Archive tier is the most cost-effective solution for long-term retention of rarely accessed data.

By carefully analyzing your data usage patterns and selecting the right storage tier, you can significantly reduce your Azure storage costs. Moreover, Azure offers automatic tiering options like blob-level tiering and life cycle management policies, which can further optimize your storage costs based on your data lif ecycle.

5. Leveraging Azure Hybrid Benefit

If you’re an existing Microsoft customer, leveraging Azure Hybrid Benefit can be a game-changer for your Azure cost optimization. Azure Hybrid Benefit allows you to bring your on-premises Windows Server and SQL Server licenses with software assurance to Azure, offering significant cost savings.

With Azure Hybrid Benefit, you can run Windows Server and SQL Server workloads on Azure at a reduced rate, providing substantial savings as compared to pay-as-you-go prices. Furthermore, Azure is the only cloud provider that offers such benefits, making it an ideal choice for businesses looking to optimize their cloud costs while leveraging their existing Microsoft investments. Azure Hybrid Benefit is starting to support software from other companies, including Oracle and Red Hat.

6. Regularly Reviewing and Optimizing Subscriptions

Lastly, regularly reviewing and optimizing your Azure subscriptions is a must for Azure cost optimization. This involves keeping track of your Azure usage and costs, identifying any inefficiencies and making necessary adjustments.

Azure provides several tools like Azure Cost Management and Azure Advisor that can help you gain insights into your Azure spending and offer personalized recommendations for cost optimization. For instance, Azure Advisor can identify idle resources that can be shut down to save costs or suggest reserved instances for predictable workloads to avail discounts.

Moreover, consider exploring Azure Cost Management Power BI App for advanced reporting and analysis of your Azure spend. It offers a rich set of visuals and filters that can help you uncover deep insights into your cost data and drive cost efficiency.

In conclusion, while Azure offers a plethora of services and capabilities, managing costs effectively requires strategic planning and continuous monitoring. By implementing the above strategies, you can ensure that you’re making the most out of your Azure investments while keeping your costs under control.

February 1, 2024
Consider Performance, Growth & Budget When Buying Data Analytics
So, your business needs to invest in data analytics technology to improve efficiencies, competitive advantage or business outcomes. There are a ton of things to consider, but underlying each decision are three driving factors:
- Performance – The need to meet service level agreements.
- Growth – The need to accommodate success, as well as deal with inevitable industry changes.
- Budget – The need to do both of the above while keeping costs low enough to not erode the profit gain from analytics.
These three forces underpin nearly every technology selection decision, but what frequently isn’t noticed is how much these three drivers interact.

1. Concurrency and Growth

Test both for current levels of concurrency and the level you hope to achieve in the next few years as the organization grows.

When evaluating benchmarks between vendors, consider that benchmarks are designed to make that company’s software look good. For example, if they are good at concurrency, you will see various levels of concurrency represented in the benchmark. If the benchmark shows only one workload at a time, or maybe ten, you can safely assume that concurrency is probably not something that technology is good at. Similarly, if the benchmark is done at 10 TB scale, the vendor probably isn’t that good at high-scale analytics.

When bringing vendors in for a proof-of-concept, one mistake I’ve seen (more times than I can count) is testing the capabilities of the software with only one user at a time. People do not line up politely to use analytics one at a time.

In addition to current levels of concurrency, over time, hopefully, the organization will grow, and the number of both internal analytics users and external customers will increase. Testing for the number of users you have now may not uncover problems that will invariably reveal themselves when a lot of people hit the system at once. The last thing your organization needs is to turn away customers because they’re overloading your systems.

2. Performance & Price

Evaluate price/performance, not performance alone.

Everyone understands the importance of performance. Not one user has ever gone to a data architect or engineer and requested for their analytics to “please execute more slowly.” But performance isn’t simply how fast the analytical software can process queries, how fast the data pipelines can move data or how fast the response is between data input and reaction output. There’s also a monetary aspect of performance to bear in mind.

In a recent benchmark, three data management and analytics stacks were compared with 60 simulated concurrent users/workloads. The difference in queries per hour on 250 TB of data was minor, perhaps 16 queries per hour for the slowest and 23 queries per hour for the fastest.

(Mcknight Benchmark – SaaS Data Analytics Platform Comparison – vendor names removed)

It looks like performance is just not that big a consideration for this technology. But there is no such thing as an unlimited budget. Let’s look at how much it would cost to get this level of performance out of each stack.

(Mcknight Benchmark – SaaS Data Analytics Platform Comparison – vendor names removed)

Price-performance is a far more useful metric of value to the organization. How much the software can do is irrelevant if the budget limits how much the business can afford to do with it.

3. Software Efficiency

Consider how much efficiency and control you’re willing to trade for ease-of-use.

When you analyze data in the cloud, you’re not just paying for software, you’re also paying for hardware, a.k.a. cloud compute instances. Bundling the two costs in one bill makes things easier. But it also means that cloud providers make more money the more instances, or compute nodes, you use. You trade ease-of-use in billing for a higher price. And they no longer have a financial incentive to provide efficient software.

Similarly, to make a cloud-based analytics software scale up in performance and concurrency with zero effort on your part, the software has to use only defaults for all settings internally. It can scale only by throwing more compute at the problem; compute that you’re paying for every time you use it. You’re trading control of the software–tuning, scaling guidelines, shut down conditions, etc.–for ease-of-use, again for a higher price.

Throwing more compute at a problem isn’t always the best solution. Recently, I saw a POC where the customer implementation included 278 EC2 nodes on Amazon cloud. The organization didn’t initiate the POC because of inefficiency. They were having performance problems, even with that much compute power. A competing product was able to run on only nine EC2 nodes with the same workload and better performance. The company was paying 25 times as much for the compute hardware because it was convenient.

Be aware of the tradeoffs.

4. Affordable Scalability

Paying for only what you use can become impractical when you use more and more.

The volume of data that is being created, consumed and captured is growing exponentially. By 2025, it is estimated that nearly 30% of data being generated will be real-time. Instead of pulling data in batches, data will be pulled in continuously. Queries will be responded to in seconds, not hours, or in milliseconds, not seconds.

Going to the cloud can make tremendous sense when a company or a workload in that company is new. But studies show that as businesses scale and growth slows, the pressure the cloud puts on business margins eventually outweighs its benefits. This is why most enterprises today are considering repatriating some or all of their workloads off the cloud.

5. Flexibility for Change

Make certain your stack will continue to work even as conditions change, and you won’t have to rebuild from scratch to do the same thing in a different location.

When you’re building a long-term architectural strategy, you want to ensure you cover as many bases as possible because, the fact is, you really don’t know what the future holds. Ten years ago, maybe you had a Hadoop on-premises strategy or a data warehouse appliance. Today, you may have a cloud-focused strategy. Tomorrow, maybe you’ll move some or all of those workloads back on-premises due to performance, security, costs, regulations or other reasons.

This is why you want flexibility that doesn’t mandate a “cloud-only” or an “on-premises-only” or a “this-cloud-only” architecture and which doesn’t integrate with only the same vendors’ software. You want an architecture that can work equally well both on the cloud as well as on-premises, hybrid or multi-cloud, providing the flexibility of going where business needs are best met.

Containerization offers possibly the highest level of flexibility in deployment, but it can also add to deployment complexity, so again, be aware of what you’re trading. If the software you choose is platform-agnostic—not tied to any particular location, ecosystem or deployment model—then that will make future choices a lot more flexible.

Regardless of what analytics you choose, what you decide to build or what use cases you have to meet, striving for balance in performance, growth and budget will create a strong data architecture, now and for the future:
1. 1. The analytics architecture is high-performance: it should meet SLAs, get things done on time and meet or exceed expectations and requirements.
  2. The analytics architecture is resilient to growth and change; even if there is rapid growth or sudden or extreme changes, it’s future-ready.
  3. The analytics architecture should control costs and live within an allocated budget.
Keep these guidelines in mind when choosing an analytics provider. The decisions you make today will have direct ramifications on the growth, profitability and success of the business tomorrow.
May 9, 2023