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Category: Continuous Delivery

Continuous delivery is a software engineering discipline that allows organizations to consistently develop and release quality software at a rapid pace. It is achieved by automating the software development lifecycle, enabling tasks such as development, testing and release to occur concurrently and continuously.

  • Building Scalable Cloud Applications With MySQL

    Building Scalable Cloud Applications With MySQL

    Relational database systems such as MySQL have long been the go-to choice for handling large and complex data handling tasks. But, with the introduction of new technologies like NoSQL, many developers started to question whether traditional relational databases still have the upper hand. However, when building high-scalability cloud applications, relational databases like MySQL still have the edge over NoSQL. Here are five reasons MySQL remains superior to NoSQL in supporting developers of high-scale cloud applications.

    1. Enablement of Complex Queries

    Structured query language (SQL) is the most widely adopted language for relational databases, and MySQL is no different. SQL gives developers a powerful platform for creating complex queries and ad hoc reports, efficiently managing large datasets and creating tables and indexes for data optimization. By contrast, NoSQL usually offers only rudimentary query and data manipulation capabilities, often proving inefficient when handling complex data sets. Most data analysts are also familiar with SQL, so it’s a drop-in tool they can use to help gain insights.

    2. Scalability and Reliability

    MySQL is noted for its scalability when handling massive data loads and is particularly well suited to cloud-based applications that require consistently high performance. MySQL ensures that the consistency of data is maintained. MySQL is the go-to option for scalability and reliability for larger cloud applications. Companies such as Facebook, GitHub and WordPress have built billion-dollar businesses on MySQL, and it’s been tested and validated in some of the harshest and most demanding workloads of any database.

    3. High-Performance Replication at Scale

    MySQL replication offers a reliable solution for cloud applications that need to scale. Unlike other databases, MySQL’s replication capabilities provide effective data safety, making it a robust choice for applications that require high availability and durability. Additionally, MySQL enables seamless version upgrades without disrupting operations, ensuring the system always has the latest features and security patches. The read scaling feature of MySQL improves performance by distributing the read load across multiple instances, making it ideal for large-scale cloud applications. With a proven track record at scale, MySQL replication is the optimal choice for applications that want to grow and scale efficiently.

    4. High Availability and Durability

    MySQL provides enhanced high availability and durability, ensuring that critical data is always available even during maintenance and disaster recovery. This is because MySQL is fully ACID-compliant (atomicity, consistency, isolation, durability) and provides full support for transactions. Even when the system fails, the transaction can be rolled back and the data is not lost. With NoSQL databases, data is primarily written in memory and doesn’t provide the same degree of durability or consistency.

    5. Ease of Implementation and Debugging

    MySQL is easy to install, implement and debug compared to NoSQL. MySQL is supported by a large community of developers and database administrators who use it for a diverse range of applications. MySQL is also open-source and free to use, making it a great choice for businesses of all sizes. NoSQL systems require the installation of additional tools, libraries, and other components for implementation, making it more complex and time-consuming.

    MySQL provides many benefits for developers of high-scale cloud applications, ranging from its powerful SQL language for complex querying to its high availability and flexibility for managing multi-table joins. NoSQL remains a viable option in some cases, but developers who are building high-scale cloud applications are mainly sticking with MySQL due to its scalable and reliable nature, easy implementation and flexible query-handling capabilities. Choosing the right database engine is critical for any organization that relies heavily on large and data-heavy applications. MySQL continues to stand the test of time when it comes to ensuring performance and getting consistent results.

  • How Event-Driven Architectures Drive Real-Time Operations

    How Event-Driven Architectures Drive Real-Time Operations

    People, events, the human brain—in fact, the whole world operate in real-time, but businesses have struggled to keep up. With the help of event-driven architecture (EDA) and the Open API economy, businesses can now do the same. The power of an event-driven world means that, after years of geopolitical events affecting how businesses operate, many businesses are starting to uncover real value by truly being able to operate in real-time.

    Whether it be retail and manufacturing or energy and resources and financial services, locating and responding to vital issues within a company’s supply chains or product lines in real-time, is key to success.

    Amazon’s CTO, Dr. Werner Vogels, said that “the world is event driven” in his keynote speech at AWS re:Invent in December 2022. Now, new IDC research unveils that nine out of 10 of the world’s largest companies will deploy real-time intelligence driven by event-streaming technologies by 2025.

    But What’s the Secret Behind Such Success?

    A recent IDC Infobrief, sponsored by Solace, surveyed over 300 enterprise IT professionals in North America, Asia and Europe, all of whom work for large companies implementing or considering EDA. The results are quite telling–an overwhelming 93% of respondents at companies that have deployed EDA across multiple use cases said EDA has either met or exceeded their expectations. In addition to technical advantages from EDA, most businesses also see clear business benefits: A full 23% of respondents reported increasing productivity; 22% said better customer acquisition and 18% saw revenues increase as a result of EDA efforts.

    1. Get Support From the Top to Ensure Alignment Throughout

    Expanding the footprint of EDA across the enterprise is a journey, and every journey starts by assembling those that are critical to its overall success. Business sponsorship and engaging key stakeholders is vital, especially in the early days of EDA adoption – 56% of respondents in the early EDA stages cited this as a priority when ROI and business benefits may not be immediately clear.

    The impact of well-aligned C-suite, operational and technical teams is reflective of business-level digital maturity, too. As 35% of respondents at an advanced stage of EDA rollout felt C-level support was critical, it comes as no surprise that respondents with higher levels of EDA maturity also have higher levels of overall digital maturity, including digital strategy and change management support.

    2. Tackle Complexities Head-On With the Backing of IT

    As EDA becomes more pervasive across an organization, demands on IT become more sophisticated, requiring a deepening of EDA skills in the IT organization, notably with DevOps teams, developers and architects. More than one-third (36.1%) of respondents cited the lack of skills to execute EDA as a hurdle to adoption. Approaches to logging, governance and oversight (30.7%) can also become increasingly challenging and must be thought through carefully.

    This is where EDA providers themselves need to step up and provide adequate training and a certification path for architects DevOps and developers looking to gain the fundamental knowledge and skills to design and implement event-driven systems. This should include technical details such as understanding various design patterns for EDA, microservices choreography versus orchestration, the saga pattern and RESTful microservices. Education should also clearly define and demonstrate key concepts and tools for EDA success, such as event portal, topic hierarchy best practices and event mesh.

    3. The Benchmark for Success Chops and Changes: Businesses Need to Go With the Flow

    The right measures of EDA success in the early days of adoption are not the same measures as EDA adoption grows over time.

    Fewer EDA-mature organizations cited “cost reduction” (23%) and “number of projects completed” (31%) as top measures of success. In the medium term, after two or three use cases, most organizations saw “operational stability” along with “number of projects” to measure success. Further, after broad adoption, “increased revenue” (43%), “operational stability” (32%) and “amount of resiliency” (30%) become more important measures.

    This changing set of measures is reflective of the maturity curve of EDA adoption across multiple applications within a business’s ecosystem. A business is truly operating in real-time when deploying EDA across key customer-facing, employee-facing and supplier-facing organizations. This is where revenue is being generated in high volumes, organization-wide – hence stability and resilience become key to ensuring things continue to run smoothly on what can often be a global scale.

    4. Keep Everyone in the Loop

    It is essential to take the company with you along the entire journey. The research showed the bumps in the roadmap. In the early stages of EDA maturity, lack of understanding of EDA benefits and inconsistent buy-in are the most frequently cited organizational challenges (38%). As organizations progress to a centralized EDA status, cost concerns (42%) and finding the right use cases (36%) can hamper success. More advanced stages of EDA also cite a lack of understanding of EDA benefits (45%), and cost concerns (39%) but change resistance (38%) becomes a major hurdle.

    Continuous focus on change management and communicating business benefits is vital. The core group of invested stakeholders who began the journey must band together to demonstrate the value of EDA clearly and consistently to other areas of the business on a regular basis.

    5. Recognize the Benefits That Partners Bring to the Table

    To accelerate business and technical benefits and reduce the impact of challenges, survey respondents cited “finding a supportive partner to assist with the implementation of EDA” (37.7%) as a critical consideration. Partnerships and product integrations with the providers of preferred business software and SaaS services can make it easy to event-enable an organization. Given the amount of new technical skills and learning previously cited, this can provide peace of mind for organizations taking their first steps on the journey to EDA.

    EDA isn’t just a change in IT architecture, it’s a mindset that applies to modern business leadership organization-wide. To keep the momentum during the journey, respondents also noted the use of a robust change management plan that “ensures coordinated middle management support” (35.1%), as they are typically accountable for getting work delivered and reporting across the organization.

    EDA Becomes the Norm

    The InfoBrief results speak for themselves – EDA is quickly becoming the “normal” process for businesses looking to operate in real-time. As more and more companies recognize the business benefits at stake, understanding these five requirements will be a necessity for successful EDA deployment.

  • GraphQL API Visibility Ensures Enterprises Can Escape Lock-In

    GraphQL API Visibility Ensures Enterprises Can Escape Lock-In

    While GraphQL is still early in its enterprise adoption curve, the runtime query language (and replacement for REST APIs) has already built an impressively robust ecosystem for jumpstarting major enterprise-grade deployments. Among the appeals of GraphQL are its open source implementations and breadth of available server types, which combine to offer enterprises flexibility and the benefits of best-fit solutions.

    However, operating GraphQL in production, maintaining GraphQL APIs at enterprise scale and achieving the requisite GraphQL visibility and security require complementary tools and services. This is where enterprises can fall prey to vendor lock-in and lose the flexibility to change and control their own deployments if they aren’t careful.

    Enterprises need vendor partners to manage their GraphQL deployments effectively, and vendors are glad to offer comprehensive SaaS solutions. But enterprises must understand that a vendor can seek to capture their long-term business by coercion—straitjacketing customers by hosting their entire GraphQL infrastructure and GraphQL gateway and making it, well, not exactly easy to let go. They can unleash particularly nefarious practices, using proprietary features to force customers to migrate to certain technologies or purchase expensive upgrades to keep their crucial GraphQL deployments afloat. Enterprises must be wary of allowing this vendor lock-in to happen for their own good.

    Knowledge is essential to maintaining the balance of power in vendor relationships. Enterprises must understand their GraphQL graph and key measures to correctly assess current vendors and maintain agility and control over deployments by not entrusting their entire fate to any one partner.

    These are the specific areas where enterprises should seek out intelligence and reliable metrics in order to choose their own future with GraphQL:

    Understand Your Overall Graph (and Subgraph) Utilization

    Establishing an accurate overview of your graph utilization—and harnessing actionable insights—are crucial, foundational steps that lay the groundwork for deeper analysis and better decision-making. You need to know what graph and subgraph objects and operations your most important API users heavily engage with and which objects and operations are underused or not used at all. You need visibility into who is using GraphQL APIs and how. Getting to actionable intelligence should also tell you where errors are most likely to occur and what’s causing them, as well as where major performance bottlenecks pop up during heavy load events.

    With this overview available, the next steps call for building a depth of knowledge in each of these five areas:

    1) Understand areas of heavy graph and subgraph usage

    Knowing exactly where heavy usage occurs in your graph puts you in a position to upgrade or migrate your GraphQL API server or gateway on your terms while mitigating outage and error risks. Specifically, you want to know which operations in your graph are executed most and how often, which graph objects and fields are consumed most often, and which subgraphs support those most heavily burdened areas in your supergraph. This knowledge and some careful planning help to put successful GraphQL server or gateway changes within your power and also reduce risk when introducing changes to areas of the graph under heavy consumption.

    2) Understand where your graph is underused

    GraphQL migration and modernization efforts are simpler—and carry less risk—when you first remove any unused functionality and reduce your scope as much as possible. To do so, you need visibility into your graph’s least executed operations, objects and fields, and subgraphs, as well as any operations with zero recent usage. Then, flag low-use graph areas you can deprecate, replace or just remove to simplify your deployment before making changes.

    3) Understand your GraphQL API users and usage

    You want a seamless experience for your GraphQL API users throughout any changes you make, especially for the users and graph-usage patterns most crucial to your business. That means knowing the frequent users of the areas of your graph under the most heavy usage. You also want to recognize and bolster any GraphQL operations that your most important users frequently call, in addition to the objects and fields those users consume.

    4) Understand graph errors and potential error hotspots

    The right actionable intelligence will prepare enterprise teams to anticipate and address graph errors. This requires visibility into where, when, why, and how often graph errors occur and error hotspots (for example, high P95 latencies indicative of potential timeouts). Insights into which users feel the brunt of graph errors are also valuable in shaping mitigation strategies.

    5) Understand graph performance bottlenecks

    Bottlenecks caused by your GraphQL server or gateway itself may call for a shift in your graph’s underpinnings. Bottlenecks can also arise from costly queries of substantial depth and height, especially when these queries see intensive use.

    To foresee and address bottlenecks, actionable insights include the average and P95 latencies of your graph’s most-called operations and the heights and depths of your graph queries with the worst performance metrics. You also want to know the number of times that bottlenecked operations get called each day, the subgraphs at the root of bottlenecks, the latency added by supergraph query planning, and which users are impacted the most by bottlenecks.

    Graph Knowledge = The Power to Avoid Vendor Lock-In

    Implementing the GraphQL API visibility and actionable intelligence strategies covered here help ensure that an enterprise has the means to modernize or migrate as necessary to preserve its strategic independence. Those unfortunate organizations already in the grip of vendor lock-in may need to bide their time but should still use these same techniques to improve and decouple their fundamental GraphQL services from their vendor-controlled GraphQL technology. There’s no acceptable reason why organizations relying on free and open source GraphQL servers and gateways should find themselves stuck in proprietary software arrangements. Thankfully, the right knowledge can deliver enterprises a more flexible future as they modernize API development with GraphQL.

  • Raspberry Pi 5: Faster, Better, Stronger — Spendier

    Raspberry Pi 5: Faster, Better, Stronger — Spendier

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    In a cheeky extra post this week: Everyone’s favorite single-board ARM computer, the Raspberry Pi, has a new generation coming soon. Compared to the ’4, RPi5 has double the performance, quadruple the base RAM and far more capable I/O. (more…)