Can you name a common promise that never comes to fruition? We have one – technology will eventually get simpler. Take the cloud for instance. At one point, this technology sounded as straightforward as could be. Just lift and shift business-critical applications from a legacy data center to a cloud provider! No more hardware or virtual infrastructure to manage and support! 

Truth is, modernized cloud application environments are highly complex, so much so that internal IT and data center monitoring tools can’t handle it without the right resources. Without these, IT operations teams run blind.

Why The Complexity?

Why are modern applications so complex today? Unlike monolithic applications that were hosted by individual VMs in an on-prem environment, modern applications are broken down into microservices that are each assigned a defined task or capability. Each container acts like a tiny server, which multiplies the number of endpoints that require monitoring. On top of that, many companies utilize multiple clouds to match each of their critical apps with their optimum cloud environment.

Companies believe this complexity is worth it because it allows for incredible agility to respond to fluctuating dynamic workloads and to serve users at a scale that monolithic applications could never achieve. For all these wonderful benefits, however, there are some real challenges:

• Container Orchestration: Applications are hosted within so many containers running in different environments.
• Security: Containers are more prone to security threats due to vulnerabilities, insecure configurations, and supply chain attacks
• Integration: Modernized container applications often integrate with other applications and services that require a deep understanding of different systems and interactions.
• Monitoring and Troubleshooting: Companies have invested heavily in monitoring tools over the years, but traditional monitoring tools don’t work in the dynamic world of speed and scale that cloud computing enables.
• Multiple Clouds: The use of multiple clouds creates learning curves for support personnel that must rotate through portal admin consoles.

The complexity of container ecospheres doesn’t stop there. Most companies that employ the cloud still utilize on-prem environments. Some of this is due to legacy applications that cannot be modernized. To avoid cloud lock-in, some organizations store their data in a separate data center adjacent to the cloud to avoid data transfer costs if they change cloud providers. Despite the complexity of it all, the benefits that modernized applications bring cannot be ignored. It is one of the reasons why predicts that almost two-thirds of spending on application software will be directed toward cloud technology in 2025.

Internal IT Requires The Right Tools To Support The Cloud

There’s no doubt that IT teams are developing legitimate value-added innovation and containers can make this process easier. Developers can deploy microservices in different languages and technologies while time to market is reduced with added functionality. But all this innovation can’t be fully leveraged without the proper support from IT operation teams. For many organizations, IT operations aren’t modernized to do the job because the data center monitoring tools they are saddled with are not applicable to cloud applications.

• Infrastructures of data centers and cloud environments are fundamentally different. Data centers reside in a fixed location with dedicated hardware while cloud environments are distributed across shared hardware over dispersed locations.
• Data center applications often have static predictable workloads whereas cloud applications are highly elastic and scalable. Traditional monitoring tools may not be designed to keep up.
• Cloud applications are API-driven, and many traditional monitoring tools aren’t optimized for them.
• Traditional monitoring tools can’t act fast enough due to their reliance on human intervention and dashboard rotation.

When you consider everything, you begin to understand why say that monitoring containerized microservices in real-time is almost impossible.

How AIOps Makes Monitoring Containerized Microservices A Reality

It is possible to monitor containerized microservices to ensure that your cloud-based applications run optimally. But how? The answer is AI automation. Gartner states that many IT organizations who fail to adapt AI will no longer be operationally viable. Only automated AI systems can handle the scale, speed, complexity, and dynamic nature of today’s modernized applications that rely on cloud-hosted containers and microservices.

• AI monitoring can perform root cause analysis, enabling problems to be identified and resolved at speed.
• AI monitoring can handle large data sets from disparate systems and recognize when related anomalies occur within an environment. This helps prevent alert storms.
• When implemented into your integration and deployment pipelines, AI monitoring can ensure that problems are detected so that remediation or roll back processes can be implemented instantly.

In 2022, Forrester evaluated 11 AI for IT Operations (AIOps) providers and named Dynatrace a in that industry, giving them top scores in the Current Offering and Strategy categories. AIOps provides the ability to leverage machine learning and other AI technologies to automate and improve the performance, availability, and security of IT systems and applications. It only makes sense that a new application architecture requires a new operational approach.

Contact WEI to find out more how Dynatrace has the solutions you need to keep your IT operations in pace with your application innovations.

Next Steps: Thanks to Dynatrace, full stack application analytics and observability is fully achievable for your AWS-hosted application environments. Converting terabytes of data about your cloud application environment and converting it to real answers and actionable, intelligent automation, companies can maximize their modernized application strategies.

In this tech brief, we expand on:

• Application Modernization
• Cloud scalability
• Monitoring vs. observability

The post Why Modernized Applications Also Require Modernized IT Operations appeared first on IT Solutions Provider - IT Consulting - Technology Solutions.

It’s Tuesday and you are waiting for work colleagues to join you at lunch for a quick reprieve from the office. You pull out your smartphone and begin browsing to pass the time. An interesting technology article catches your eye and you tap to access the page. Unfortunately, the session times out and your engagement with that journey ends prematurely. Does this experience sound familiar?

According to a recent Google study, 53% of mobile users will abandon a session if it takes longer than 3 seconds to load. Fair or not, this is the bar that has been set, and serves as a reminder to enterprises of how important it is to modernize applications. Once users leave you behind, it is difficult to get them back as 79% of participants in the same mentioned study said they will not return after a negative experience.

What Makes an Application Modern Today?

Applications used to consist of one singular block of monolithic interdependent code hosted on a single virtual machine (VM), a design considered innovative in its day. But things are different now. To gain greater agility and flexibility, companies hastily transitioned to microservices and container environments. Here, a single application is broken up into small individual modules where each module performs a single defined task or capability. These services are then coupled together to communicate with one another, creating a highly flexible coalition of services that we call the modern application. Here, all necessary components are then contained within a single container.

Benefits of Application Modernization

Application modernization provides greater flexibility as microservices can be deployed in different programing languages and technologies. Modern applications are far more resilient as containers can be easily migrated or deployed to other systems. Updating is easier as each service can be updated and deployed independently of others and new application features and functionality can be released more rapidly to market. Containers and the microservices they host can be scaled up or down to meet fluctuating workload demands in real time.

The 6 R’s of Application Modernization

So, how do you go about updating monolithic and legacy applications to the modern era? AWS created a set of six best practice strategy options that be applied to any business application you may consider modernizing.

1. Retain: Keep the existing application in its present form as it still meets the needs of the organization.
2. Refactor: Improve the code and architecture of the existing application to attain greater scalability and flexibility.
3. Rehost: Move the existing application to a new infrastructure, such as a cloud platform, without changing its code.
4. Replace: Replace the existing application with a pre-built solution or different technology.
5. Rebuild: Create a new application from scratch to replace the existing one.
6. Retire: Discontinue support for the application and retire it. The application is no longer needed

The Paradox of Application Modernization

The speed, dynamics, and scalability of modernized applications will outpace and out scale traditional management and monitoring tools. While they may have been sufficient for an on-prem legacy environment, their product cycle is ending. If your applications are delivering workloads differently, it only makes sense that they need to be managed differently. It isn’t just programmers who need greater agility to increase the velocity of new feature releases and updates. The application admins need greater speed and agility to ensure application environments are always optimized. If not, they will fail to attain the full benefit potential of modernization efforts, thus diminishing ROI and risking losing users along the way.

Monitoring vs. Observability

Monitoring and observability may sound alike, but one is superior in scope to the other. Monitoring was appropriate for traditional on-prem environments. It helped IT personnel track problems, issues, and performance using a list of prescribed metrics that provided a snapshot of the systems that comprised the application environment.

While sufficient for the application models of yesteryear, monitoring no longer cuts it for today’s cloud application environments. The architecture that interconnects an application’s services and interdependencies together is highly complex and visibility is a challenge. Enter observability.

Observability takes monitoring to the next level by aggregating and analyzing data from multiple sources and uses AI intelligence to put the puzzle pieces together. Observability isn’t restricted to alerts and metrics. It also provides insights and context to your environment so IT can properly understand the issues at hand. While monitoring provides a view into your application environment, observability provides full comprehension and understanding.

Intelligent Observability with Dynatrace and Davis

Meet Davis (short for Davis AI-Powered Detection and Response). Davis is part of the Dynatrace performance monitoring and management solution platform for modern applications and cloud environments. Davis uses AI and ML to identify and prioritize issues and security risks in real-time on its own. Besides delivering comprehensive contextual insights to your support team, the platform automatically remediates issues before users are affected and IT can review them. Don’t just upgrade your applications to the modern era, upgrade your application operational tools in tandem with Dynatrace.

Next Steps: Thanks to Dynatrace, full stack application analytics and observability is fully achievable for your AWS-hosted application environments. Converting terabytes of data about your cloud application environment and converting it to real answers and actionable, intelligent automation, companies can maximize their modernized application strategies. We expand on this in our free tech brief,

In this tech brief, we expand on:

• Application Modernization
• Cloud scalability
• Monitoring vs. observability

The post Application Management: Keep Pace With Your Application Modernization appeared first on IT Solutions Provider - IT Consulting - Technology Solutions.

How much are utilizing the cloud to support your business initiatives? Cloud environments offer immense benefit, especially as hybrid workforces gain traction. However, they also create unique challenges that legacy software, hardware and strategies are ill-equipped to handle.

One such challenge comes in the form of observability, or more specifically, the lack of it in cloud environments. Observability offers the chance to utilize collected data to improve user experience, reduce downtime, detect other issues that could negatively impact business, but traditional observability strategies just can’t keep up with today’s cloud environments.

In this second article in our two-part series on advanced observability, we’ll discuss how is addressing these challenges and what these solutions can do for your enterprise.

Learn more on this topic by checking out part one here.

Utilizing Automation For Scalability

In part one, we discussed some of the challenges associated with observability at scale. The problems can largely be boiled down to the following:

• The complexity of cloud environments.
• The ever-increasing volume of data and alerts.
• The resource and time commitment associated with monitoring microservices and containers.
• Siloed data.

According to a report from Dynatrace, “95% of applications in enterprise organizations are not monitored due to siloed tools and burdensome manual effort.”

A common solution is to try and tackle observability through adopting multiple siloed monitoring tools, but this approach only results in wasted resources and wasted time. Instead, enterprises must transform the way they collect and utilize data through artificial intelligence (AI) and .

Dynatrace is tacking this problem to offer enterprises continuous, automatic data collection and analysis, which translates to enterprise-grade scalability and end-to-end observability.

, which collects all monitored data within the environment, also automatically detects all applications, containers, services, processes, and infrastructure on start-up and in real-time. Instrumentation is also automatic, with zero configuration or code change. Data collection, including high-fidelity data like metrics, logs, and user experience data, begin as soon as the system component becomes available.

Auto-baselining is also included, with Dynatrace’s smart baselining adapting dynamically to environment changes. Finally, and perhaps best of all, updates are automatic as well, reducing ongoing maintenance through continuous, automatic, and secure updates throughout the entire environment.

Getting Context From Your Data

In environments where data is siloed, assessing the health of the system as a whole can be next to impossible. Alerts that may have a common cause can go unnoticed and the underlying issue unaddressed. For this reason, Dynatrace has prioritized offering contextual metadata to help administration teams understand what the raw data is telling them.

Using this metadata, Dynatrace creates a real-time topology map, which captures the relationships and dependencies for all system components up and down the stack, as well as horizontally between services, processes, and hosts. This map reveals the actual causal dependencies for the collected data, and also acts as a key foundational piece that enables the strategic use of AI in observability.

AI Offers The Answers IT Teams Need

Dynatrace’s AI engine, , takes the burden off of IT teams and automates anomaly root-cause analysis, reducing the manual efforts required for advanced observability.

To set it apart from other AI platforms, Dynatrace prioritized the following when designing Davis:

• Precise code-level root-cause analysis, which allows Davis to pinpoint malfunctioning components in milliseconds.
• Identification of bad deployments to offer the exact deployment or configuration change that caused an anomaly.
• Looking beyond the unknown. Davis looks beyond predefined anomaly thresholds to detect any unusual “change points” in the data.
• Automatic hypothesis testing before making real-time decisions.
• Removing repetitive model learning or guessing to move beyond machine learning approaches.

All in all, Dynatrace is reducing the manual aspects of advanced observability, making it simpler and easier for enterprises, regardless of the scale or complexity of the IT environment.

Ready for Advanced Observability?

As a leader in software intelligence, Dynatrace is simplifying cloud complexity and accelerating digital transformation for enterprises around the world. Instead of just more data and more time spent gathering it, Dynatrace offers solutions that help enterprises use the data they collect and offer improved business outcomes. Find out what you could be missing from your data and processes — contact WEI today to learn more about what’s possible with the Dynatrace platform and how you can leverage it for your business.

NEXT STEPS: Find out how Automation and AI is helping companies accelerate innovation for their customers and for their business. Check out our tech brief below to learn more.

The post How Observability with Dynatrace Can Improve Business Outcomes, Part 2 appeared first on IT Solutions Provider - IT Consulting - Technology Solutions.

How familiar are you with observability? The concept has gained traction as enterprises digitally transform their IT environments and embrace the cloud. For many companies, observability offers the chance to utilize collected data to improve user experience, reduce downtime, detect other issues that could negatively impact business, and more.

However, traditional observability strategies just can’t keep up with today’s cloud environments. The rapidly increasing size and complexity of these environments dwarfs manual instrumentation and performance tools, especially as enterprises need complete visibility into every component of their environments.

So, how can today’s enterprises achieve the level of observability they need, and most importantly, utilize their data to improve business outcomes? In the article below, we’ll discuss how Dynatrace is addressing these challenges and what these solutions can do for your enterprise.

Getting Answers Out Of Your Data

As shared in a from Dynatrace and WEI, observing data is just to start. By properly utilizing the observed data, enterprises can shift from just collecting data to using it to make decisions that produce the business outcomes they need to be successful.

However, actually poses a problem. Some IT teams try and tackle observability through adopting multiple siloed monitoring tools, which inevitably leads to wasted resources, wasted time spent on monitoring and manual configuration, and struggling to collect and share data between tools. To properly monitor applications at the enterprise level, companies need to transform the way they collect and utilize data.

To address this need, Dynatrace developed their , which expands on traditional observability through automation and artificial intelligence (AI) to allow it to scale to the largest and most complex of environments.

Through this platform, enterprises can utilize the built-in AI-assistance to continuously to detect anomalies, improve IT productivity, and give IT more time for business innovation.

Cloud Environments Demand More

While application performance monitoring has always existed, legacy solutions were built for a time when life, and the enterprise, moved much slower. Software updates were an annual event and infrastructure was contained on-premises.

Today’s IT teams have a different world to contend with. Cloud adoption requires IT to be flexible and ready for the unexpected. Most importantly, IT teams need to be able to predict where issues may occur, rather than waiting to react once they’ve already happened.

Advanced observability offers this and more, reducing the amount of time IT teams spend manually solving problems and keeping the lights on. Enterprise leadership expects more out of IT, and the technology they manage, than ever. Advanced observability allows IT to fulfill the needs of the modern enterprise and be a valuable, contributing part of the business, instead of just a cost-sink.

The Tools For Observability Success

Just as yesterday’s strategies can no longer be applied to today’s problems, the tools utilized by IT must also evolve.

To effectively manage the scale and complexity of the modern cloud environment, IT must rely on automation and AI. Legacy systems typically also focused only on collecting three specific data types: metrics, traces, and logs. However, this data on its own doesn’t offer the actionable insights.

To address this need, Dynatrace has developed , which is responsible for collecting all monitoring data within the monitored environment. It offers enterprises additional information, including user experience data, for “full-stack, end-to-end code-level observability.”

As shared by Dynatrace, this offers answers through three distinct capabilities:

• Continuous and automatic discovery and instrumentation, which ensures always-on coverage without manual configuration.
• Topology information, which offers context across the full-stack and for the data being observed.
• A causation-based AI engine, which offers actionable answers to problems through real-time analysis.

By combining software intelligence, automation, and AI, Dynatrace is helping enterprises make informed, intelligent business decisions, with fewer resources and time than traditional observability solutions.

Are You Looking To Start Your Journey To Advanced Observability?

As a leader in software intelligence, Dynatrace is simplifying cloud complexity and accelerating digital transformation for enterprises around the world. Instead of just more data and more time spent gathering it, Dynatrace offers solutions that help enterprises use the data they collect and offer improved business outcomes.

NEXT STEPS: Learn how Dynatrace transformed their own business and how you can too with automation, DevOps and AI in our new tech brief. Click below to start reading!

The post How Observability with Dynatrace Can Improve Business Outcomes appeared first on IT Solutions Provider - IT Consulting - Technology Solutions.

When we look at how IT technology has changed within the enterprise over the past decade, we often point to the proliferation of virtualization and the cloud. That is understandable as these technologies have played significant roles in the digital transformation of the world today. Now that these technologies have become conventional standards within the enterprise today, there is another identifiable technology sector that has emerged in importance and stature – cloud and application monitoring. The growing presence of these solutions is a testament to the fact that enterprises are realizing the substantial benefit of application and performance monitoring across networks of growing complexity.

The accelerating presence of cloud and application monitoring

The growing size of the (APM) industry is reflective of its determined value. The size of the APM market is expected to grow from $7 billion in the year 2020 to a projected size of 11.9 billion by 2027. That is a compound annual growth rate of 11.2 percent over a seven-year period. These numbers may in fact prove too conservative as the APM market was previously forecasted to cap at $5 billion in 2019 at a CAGR of 12.8 percent. We find the same accelerating trends for cloud monitoring as well that is experiencing a CAGR of 18.1 percent. This market was valued at just over $1 billion in 2019 and is projected to grow to $3.75 billion in 2027.

This accelerated growth is supported by the rising demand of cloud and mobile computing along with the technological advancement of performance monitoring. While funding costs have served as a traditional constraint in the past for growth, the biggest restraint for further growth is lack of awareness. While 76 percent of IT professionals in a survey last year said that monitoring the performance of their public cloud infrastructure is either moderately or very important, less than 20 percent said they can monitor these environments properly.

Observability and performance are essential

While enterprise managers have always relied on monitoring to some extent, APM today is proving a necessity in order to keep pace with the speed of business. That’s because the stakes are higher today, as are user expectations. While digital transformation has provided companies the means to inject continual innovation by enhancing the digital experience of its customers and employees, it has also magnified user expectations concerning those digital experiences. What’s more, in a world in which workloads can originate from anywhere and traffic loads can be scaled in real time, users have an innate dependency on their apps today like never before.

Monitoring translates into visibility. According to a report involving IT professionals from 15 countries, 48 percent of IT professional attribute delays with troubleshooting application performance issues with a lack of visibility, while 38 percent blamed it on application outages. Lack of visibility however is not a new problem however, but instead is one that has grown in correlation to expanding enterprises and network complexities.

But visibility alone isn’t exactly enough, you need advanced observability. The concept of observability is gaining rapid momentum as companies accelerate their digital transformation strategies by building out massive cloud-native environments that are hard to observe and operate due to their dynamic and complex nature. Let’s take a closer look at what observability is all about and why it’s critical.

What is observability and why does it matter?

According to Dynatrace (who in 2020 was named a leader in Gartner’s Magic Quadrant for APM for the 10th consecutive time) defines observability as:
Observability is the extent to which the internal states of a system can be inferred from externally available data. An observable software system provides the ability to understand any issue that arises. Conventionally, the three pillars of observability data are metrics, logs and traces.

Dynatrace extends this with UX and topology information. However, turning data into answers requires more than just visibility, which is why they stress the criticality of observability. Dynatrace advances observability with contextual information, artificial intelligence, and automation, removing blind spots, and fueling rapid remediation that aides in continuous delivery for superior customer experience. Essentially, they are saying that advanced observability is what turns data into answers.

Three key factors necessary for advanced observability

Observability, when combined with AI and automation, holds the promise to deliver the actionable answers needed to ensure cloud native applications work perfectly and deliver the best experience and value possible to their users.

1. Contextual information – Understand the full context of the observed data from user impact through entity interdependencies. Real-time topology mapping provides context across the full stack. captures and unifies the dependencies between all observability data in order to intelligently combine metrics, logs, traces and user experience data. This real-time entity topology map is the basis for advanced observability.

2. Causation-based AI – Provide actionable answers to performance problems through a precise root-cause analysis. Dynatrace’s AI system, known as Davis, automates anomaly root-cause analysis, even in dynamic microservice environments. Traditional monitoring tools offer little beyond dashboard visualizations, forcing manual root-cause analysis. Dynatrace is the only platform that takes the burden off human operators, by providing precise answers.

3. Automatic discovery and instrumentation – Ensure scalability and complete coverage in highly dynamic environments without manual configuration. The Dynatrace OneAgent discovers all processes running on the host and automatically activates instrumentation specifically for your stack. High-fidelity data is automatically and continually gathered in context without manual configuration or scripting, and new components get auto-instrumented on the fly.

New opportunities that observability can give to your Business

Regardless of your business, you most likely have a digital pipeline and the health of that pipeline is integral to your company’s operations and mission. Your customers depend on the uninterrupted flow of and software releases through that virtual conduit. It is your highway of value-adding innovation. When Dynatrace assigned their top talent and engineers to figure out what APM would look like in 2020, they ended up redefining the architecture and expectations of application monitoring itself. A case in point is the remediation process of their own internal software bugs. Rather than identify the full gamut of bugs for their new software releases in production, they now identify and remediate 94 percent of them in development thanks to the power of the Davis AI engine. This makes their software more dependable, which in turn makes their customer environments more reliable.

And then there is the unique ability to see into the user experience itself. With Dynatrace, you can even replay user sessions to see exactly what users see. Like a coach reviewing film, you can now fully evaluate user work sessions in order to better guarantee the performance that users have now come to expect.
Imagine having the power to know how much revenue is generated by each of your applications or having the certainty that SLAs and compliances are being met. These are part of the answers that Dynatrace can provide, making it more than just APM solution. With the opportunities it can provide your organization, Dynatrace is a revenue generating application.

What’s Next?

Whatever your traditional concept of application performance monitoring was before, now is the time to discover what Dynatrace is all about. WEI’s team is well versed in the Dynatrace Software Intelligence Platform and can help guide your team’s implementation with all best practices baked right into the process. Contact us today to learn how Dynatrace can uncover valuable data across your infrastructure”¦ in 5 minutes or less.

Continue learning more about automation and continuous delivery in our tech brief below, “How to Accelerate Your Business Transformation with DevOps and Automation.”

The post Why Observability is a Game Changer for Cloud and APM appeared first on IT Solutions Provider - IT Consulting - Technology Solutions.

The Digital Transformations that the world has undergone has led to an insatiable appetite for applications and built a robust reliance on them. This reliance on apps and infrastructure has been greatly magnified this past year by the absence of physical face to face contact stemming from remote work strategies. Because your business is dependent on applications, the performance of your business is tied to the performance levels of your applications. Now compound this with the great cloud migration, and it becomes challenging to discern what is truly happening out there with your apps and the cloud(s) in which they reside. These are but some of the reasons why your enterprise needs a Cloud and Application Monitoring solution that is built with the future in mind. Below are some of the benefits you can derive from a premier APM solution, such as Dynatrace.

1. Continuously learn your environment

Proper inventory management is imperative for any retail or manufacturing company. If you don’t know what’s in your warehouses, then you don’t know the actual financial status of your business. The key is to put all of your inventory to work. Think of your enterprise network in the same way. Beneath your critical applications is a complete underground of underlying components and dependencies that make up the application stack. Undoubtedly, there is a fair percentage of this undergrowth that your IT team isn’t aware of. Chances are, there are a number of weak links in the application chain in these gray areas. Weak links create weak performance.

A premier cloud and application monitoring solution adds clarity to the full application stack. It can map dependencies between components such as processes, services, and hosts both horizontally and vertically. This allows you and AI-driven intelligence to truly understand the call relationships between these dependencies. This knowledge then allows for an intelligence based APM solution to pinpoint potential problems that can impact performance.

2. A greater reliance on applications

People have been using applications since the dawn of the PC. The reliance that employees and customers have with their involved applications today is unprecedented, however. When there is a disruption in a Zoom, Teams, or Slack session, the meeting stops and frustration builds. When a disruption occurs within your ecommerce application, money transactions stop. When your CRM doesn’t function correctly, the help desk lights up with call. Disruption is a dirty word today when it comes to enterprise applications. That is why observability is so important. A solution such as Dynatrace, provides a that can prevent problems before users see them, thus keeping your revenue generating sessions running as expected.

3. Stop playing detective

So, here’s how the traditional application monitoring process played out. The monitoring system consistently fed your admin support team with droves of log files. That backlog required the laborious task of sifting through all of the noise in order to piece the puzzle together. Let’s face it. Your IT team doesn’t have the time for that anymore, nor does your business have the money to finance it.

While some APM solutions dress up these logs with snazzy charts and dashboards, they still don’t provide answers. That is changing, however. Modern observability solutions created for today’s digital transformation trends, such as the Dynatrace , are designed to deliver answers, not endless logs that no one wants to read. Dynatrace AI uncovers the root of the problem in order to automatically discover and prioritize answers to issues instantly. Your company doesn’t have time for disruption, nor does it have time to solve them. In some cases, problems are remediated by the time your admins are notified. That’s a major improvement from traditional monitoring processes.

4. Automate cloud operations

Why have so many enterprises migrated resources to the cloud in the past decade? One of the chief reasons is scalability. Enterprises today have the ability to match resources with workload demand in real time thanks to the ease at which servers, services and software defined components can be spun up and retired. Shouldn’t your APM solution be able to scale in equal fashion? Cloud monitoring offers you the same levels of scalability and flexibility as any other cloud-based solution within your environments. It can also provide you valuable insight into which clouds are being used for specific applications and data queries.

With Dynatrace you can simplify cloud operations through AI and automation to build and run cloud native apps faster. 

5. Compliance and SLA & SLO confirmation

While there are a great many benefits to cloud computing, there is always a presence of nagging uncertainty. How certain are you that your SLA performance agreements are being delivered? How do you know if your company is meeting its security compliance requirements? APM can help clear up these uncertainties, giving you the insights and information to show you what is truly going on within your on-premises facilities, as well as that murky location we all know as the .

6. Eliminate inefficiencies across your IT environment

A big part of managing a business is maximizing the efficiencies of the involved departments. Maximizing the efficiency of your shipping or manufacturing departments leads to greater profitability. Now think about efficiency in term of your IT environment. Maximizing the efficiencies of your application stacks can significantly enhance the digital user experience. An effective APM goes further by focusing on environment optimization, locating looping code, excess DB calls or those extra network hops that have plagued you for years. It can also eliminate duplicative work efforts for your staff by automating monitoring functions that were once manually driven. By providing granular directives to your support staff, issues can be dealt with in record time, saving you labor hours.

One more thing

We would be remiss not to talk about the power of self-healing. No, this blog is not about to take a turn toward meditation and breathing exercises. What we are talking about here is automating remediation and building reliable solutions. AI is a great tool for identifying and remediating issues, but you need a solution that enables you to use that insight to build resilient systems. Leveraging modern monitoring tools enables you to execute specific remediation actions in a much smarter and efficient way. If you give the ability to embed Dynatrace into their delivery pipeline they can get feedback right away, which enables early optimization.

Andreas Grabner from Dynatrace goes into greater detail about Site Reliability Engineering and the self-healing capabilities of Dynatrace in his blog article here:

Next Steps: In the time you have read this article, an APM could have already averted a disrupting event within your enterprise. There are a lot more than six benefits that can be derived from an intelligence based APM solution such as Dynatrace. We invite you to reach out to our subject matter experts here at WEI to find out all of the ways that a software intelligence solution driven by automation and AI can benefit your company today.

Continue learning more about automation and continuous delivery in our tech brief below, “How to Accelerate Your Business Transformation with DevOps and Automation.”

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