devopsy.kinsta.cloud

Author: Jay Menon

  • Best Practices for Digital Experience Management

    Best Practices for Digital Experience Management

    The COVID-19 pandemic put digital services in the spotlight. The winners in 2020 and beyond will be those organizations which provide awesome user experiences for online products, services and apps. There is scant room for error, as digital leaders before the pandemic have upped their game even more.

    For example, streaming service provider Netflix’s 2020 Q4 revenue reached $6.64 billion – almost $14 million more than expected – and added 8.5 million paid subscribers. The company had more than 200 million users in the quarter and saw viewership for non-English titles jump 50% during the year as U.S. viewers sought new content from around the globe.

    Companies in more traditional sectors, such as restaurants and hospitality, also grew by investing further in digital strategies. Chipotle’s 2020 revenue increased 7.1% to $6 billion, with digital sales skyrocketing 174.1% and accounting for more than 46% of sales. Target’s digital sales increased 155% in Q4 while Costco grew e-commerce sales by 91% in FY20, as online ordering and curbside pickup became the new normal.

    Digital Experience Monitoring Basics

    To manage this onslaught of online customers and transactions, IT organizations are turning to digital experience monitoring (DEM). DEM is a broad area, but it comes down to delivering the best experience for your customers and employees by monitoring your IT assets and addressing issues that arise before they become problems. DEM allows you to mimic and test the end-to-end customer and worker experience. Such solutions can be used in on-premises data centers or run in multi-cloud and hybrid cloud environments.

    There are two key methods for DEM:

    Real user monitoring (RUM): This entails using real users’ devices to measure the performance of a page. A script is injected on each page to measure data on page load performance for every request made, monitoring the interaction of an application and the users. The data shows such aspects as how an application is being used and the geographic distribution of users.

    Synthetic monitoring: This technique tests the performance of a page using an automation tool rather than users’ actual experiences. Scripts are used to simulate how a user might move through a web application and then reports are created based on that performance.

    In a recent report, Gartner analysts said DEM products are evolving, moving from a focus on performance and availability to correlating infrastructure and operations (I&O) and business outcomes. Currently, fewer than 15% of digital business initiatives will require I&O leaders to report on business metrics from digital experience; that will jump to 70% by 2025, Gartner says.

    For years, organizations have been using monitoring tools to measure various aspects of their infrastructure. For example, IT operations management (ITOM) solutions track metrics and manage alerts and events for infrastructure hosted on-premises or in the cloud, including servers, networking systems, storage appliances and databases. The data also can be used for historical data analysis and to map out trends.

    DEM is specifically focused on the end user experience, giving IT professionals the visibility to run diagnostics, fix issues and measure performance at each point of contact between the users and the application. Acquiring a new customer is an expensive effort, and a customer can be lost because of a single poor experience. DEM is designed to ensure the optimal experience.

    Getting Started with DEM

    There are two common approaches for implementing DEM:

    Point tools: Domain-specific monitoring tools track and measure different layers of the technology stack, such as networks and applications. The upside to this approach is you get more in-depth coverage from the point tools, but it can lead to tool sprawl, which impairs visibility and increases costs.

    Platform: This approach provides native monitoring for many areas and integrates with other tools, as needed, to deliver a central, unified view that makes it easier to see everything at once. However, it doesn’t include best-of-breed performance or the deepest analysis capabilities you will want in every area.

    An important first step is to identify the metrics and outcomes priorities for your organization. Then spend time researching the proper toolset for the goals you want to achieve. If you decide on deploying multiple single-domain monitoring tools, remember that you will need an integration strategy. The tools will need to easily share data and display that centrally, to deliver a holistic view of digital experience. Integration is also critical for troubleshooting and connecting metrics to a specific business service. You also will need subject matter experts in these technology domains who can ensure that the DEM tool(s) keep pace with advancements in IT infrastructure and development technologies.

    The Future of Digital Experience Monitoring

    The DEM field is evolving, with more parts of the I&O stack coming under its purview. Solutions will offer more capabilities and be easier to integrate out of the box with other tools because the end-to-end flow doesn’t stop with monitoring and collecting metrics. ITOps staff need to take action on critical alerts with efficient workflows and intelligent recommendations. AIOps and machine learning analytics are playing a growing role here.

    DEM can reduce time-to-value for customers and workers, simplify and ease onboarding to new sites and apps and ultimately increase interactions and sales. Advanced solutions can fuel predictive analytics, form a deeper understanding of user behavior to optimize websites and apps in step with user requirements and dynamic infrastructure changes. In a digital-centric world, DEM capabilities are critical to the health and future of organizations in every sector.

  • Visualization Shines a Light on IT Metrics

    Visualization Shines a Light on IT Metrics

    Modern IT departments operate in a pressure cooker. Their highly distributed infrastructures are spread across legacy data centers and hybrid and multiple public clouds. Now, the Internet of Things (IoT) and the edge are part of the mix.

    Massive amounts of data are flowing through these multifaceted environments, and it falls on IT to make sense of it all, ensuring that issues don’t become problems and that it’s viable to produce measurable outcomes for the business. Dashboards are instrumental for visualizing and quickly making sense of that data.

    Metrics – numeric representations of data measured over time – give IT operators and site reliability engineers (SREs) a window into how a system has historically behaved. That data provides insights as to how the system(s) should perform in the future, and aids investigations when something goes awry. IT monitoring tools act as giant data lakes, holding time series data, while dashboards give everyone from IT administrators to C-level executives ways to easily digest the data.

    The visualization market is evolving. We’re seeing different kinds of databases, such as Prometheus, which bring with them new tools to leverage the data. Prometheus (PromQL) is growing in popularity in the DevOps space and becoming the standard for monitoring containers and microservices because it makes it easier to manage time series data. PromQL also comes with client libraries that include four core metric types:

    • Counter: Represents a single monotonically increasing counter where the value can only increase or be reset to zero on restart.
    • Gauge: Represents a single numerical value that can arbitrarily go up and down, such as CPU utilization.
    • Histogram: Samples observations and counts them in configurable buckets. It also can provide a sum of all observed values.
    • Summary: Samples observations and provides a total count of observations and a sum of all observed values. Configurable quantiles are calculated over a sliding time window.

    Selecting Visualization Charts

    Selecting the appropriate visualization dashboard for each user is important to maximize the value of the data. There are traditional line and bar charts, single value tiles – which display a single data point at a specific point in time – and lists and gauges, which offer a single value at a specific point in time in a series.

    Newer visualization types are now becoming common to address the various use cases in ITOps and DevOps. Let’s walk through a few:

    1. Honeycombs offer big-picture views of IT infrastructure, yet also display detail. The hexagonal display mirrors those in a honeycomb, and helps DevOps pros slice and dice the data based on attributes or tags. Each hexagon represents a specific host or resource, and can be organized in logical groups of elements. The colors change when thresholds are reached, and the hexagons can be sized differently based on the value of the metric. Consider a case of many AWS EC2 instances scattered across the globe. Each hexagon can represent an individual instance, and they can be grouped based on the “region” attribute. This honeycomb chart would let administrators see how each infrastructure site is performing.
    2. Gauge metrics use a language like PromQL to set a ceiling and a floor. If the user creates alert conditions based on particular thresholds, the dashboard will indicate if a certain resource has reached its threshold by changing the color. A gauge that turns red may indicate a critical problem, for example. Managed service providers have SLAs with clients to maintain uptime. If a problem arises, a red indicator on a gauge tile lets the IT administrator know immediately that the SLA agreement has been breached, and that an issue needs to be addressed.
    3. Heatmaps provide a graphical representation of the volume of data points within bucketed ranges. The color of each cell of a heatmap directly reflects the density of certain metric value ranges. Heatmaps are used to display group trends and spot outliers, which make them useful when viewing metrics with a wide distribution of values.

    Role-Based Requirements

    Picking the right chart depends in part upon the people viewing the data. CXOs, IT managers, sysadmins, SREs, network engineers and network operations center (NOC) operators will have different, yet overlapping, requirements.

    For instance, SREs want to ensure the reliability and resiliency of the infrastructure, so, through their dashboards, they look at everything from availability and latency to performance, efficiency and capacity planning. They can quickly spot outliers like server downtimes or memory issues and immediately begin to troubleshoot.

    CXOs, conversely, don’t need to get into the weeds of infrastructure operations. They use dashboards to gain a macro view of metrics for performance over time across websites and networks. They need to understand the correlation between IT metrics and business services and applications. Dashboards should be able to connect those dots.

    Other Considerations

    Finding the right visualization option is important. Once that is done, there are some other steps to take to ensure you get the insights you need from your dashboard:

    Positioning and ordering: Dashboard tiles should be placed in a logical order, with important high-level statistics near the top and the deeper, and more granular metrics progressively moving to the bottom to give users a quick understanding of system performance.

    Design: A well-designed dashboard with consideration paid to color schemes and themes also will make it easier for stakeholders to digest and understand the data.

    IT infrastructure performance is crucial to the health of a company. Massive amounts of data streaming out of systems can help IT administrators and others keep up-to-date about that performance and the overall end-user experience. Dashboards offer flexible ways to quickly view and understand the metrics; IT organizations now have a growing range of charts to choose from that can present the data they need in a way that works best for them.