Have you used AIOPS to improve your Operational Automation and Resiliency

 

Top Technology Trends that CTOs can blindly follow

1) ComposableArchiteture

Composable Applications allow polyglot microservices-based packaged-business capabilities (PBCs) or software-defined business objects. PBCs — for example representing a patient or digital twin — create reusable modules that the IT-Business fusion teams can self-assemble to rapidly create applications, reducing time to market. Champion composable architectural principles in all new technology initiatives, including application modernization, new engineering, and the selection of new vendor services. Buy standard PBCs on application marketplaces and integrate using APIs. According to Gartner, by 2024, the design mantra for new SaaS and custom applications will be “composable API-first or API-only,” rendering traditional SaaS and custom applications as “legacy.”

2) Data Fabric/ Data Platform

The value of data has never been more valuable. But often, data remains siloed within applications, so it’s not being used as effectively as possible. Data fabric integrates data across platforms and users, making data available everywhere it’s needed.

Within inbuilt analytics reading metadata, the data fabric is able to learn what data is being used. Its real value exists in its ability to make recommendations for more, different, and better data, reducing data management by up to 70%.

Identify priority areas to introduce data fabric solutions by using metadata analytics to determine current data utilization patterns for ongoing business operations. Prioritize areas with significant drift between actual and modeled data.

3) Cybersecurity Mesh

Using a cybersecurity mesh approach, you can integrate multiple data feeds from distinct security products to better identify and respond more quickly to incidents. Digital business assets are distributed across cloud and data centers. Traditional, fragmented security approaches focused on enterprise perimeters leave organizations open to breaches.

A cybersecurity mesh architecture provides a composable approach to security based on identity to create a scalable and interoperable service. The standard integrated structure secures all assets, regardless of location, to enable a security approach that extends across the foundation of IT services.

4) Privacy-Enhancing Computation

The real value of data exists not in simply having it, but in how it’s used for AI models, analytics, and insight. Privacy-enhancing computation (PEC) approaches allow data to be shared across ecosystems, creating value but preserving privacy. Approaches vary, but including encrypting, splitting, or preprocessing sensitive data to allow it to be handled without compromising confidentiality is the art of PEC. PEC platform uses homomorphic encryption so users can conduct data searches against its extremely sensitive data, with both the search and the results being encrypted

Investigate key use cases within the organization and the wider ecosystem where a need exists to use personal data in untrusted environments or for analytics and business intelligence purposes, both internally and externally. Prioritize investments in applicable PEC techniques to gain an early competitive advantage.

5) Cloud-Native Platforms

According to Gartner, By 2025, cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives — up from less than 40% in 2021.

Lift-and-shift cloud migrations focus on taking legacy workloads and placing them in the cloud. Because these workloads weren't designed for the cloud, they require a lot of maintenance and don't take advantage of any of the benefits. 

Cloud-native platforms use the core elasticity and scalability of cloud computing to deliver faster time to value. They reduce dependencies on infrastructure, freeing up time to focus on application functionality instead.

Typical use cases are to build a cloud-native platform to create a portfolio of new digital services. For example, a bank can reduce the time to open an account to 5 minutes and add instant digital payments when using a well-architected technology platform. Deployment microservices architecture enables the integration of services such as savings, virtual debit card, and credit card services, allowing the system to easily scale to over 3.5 million transactions in two months.

6) AI/ML/Metaverse/ AR/ VR/Computer Vision

Distributed enterprise is a virtual-first, remote-first architectural approach to digitize consumer touchpoints and build out experiences to support products. While AI engineering is the discipline of operationalizing AI models, using integrated data and model and development pipelines to deliver consistent business value from AI, the use of NFT/blockchain-based metaverse builds on Web 3.0 principles to enable 'play to earn' gaming, AR/VR enabled retail e-commerce, real estate, hospitality, corporate training, induction on manufacturing shopfloors to aircraft engine simulations has seen a major boost in government and private investment.

Spectrum of SRE Implementation Models

 

A Spectrum of SRE Implementation models

A significant aspect of SRE implementation at Enterprise is around the model that will enable governance and growth at pace. In this article we will look at the Hub and Spoke model as an approach to solve the SRE scalability challenges towards applying a product management life approach that enables rapid, repeatable SRE practices that are cross-pollinated from the spokes that are usually across business domains.

 

 

The Hub & Spoke model not only decentralizes the implementation of solutions, but it also allows for rapid innovation / sharing of ideas across the organization, while centralizing research for latest best practices. It helps attract, develop, and retains scarce SRE talent, allowing for flexible allocation of resources to keep employees challenged with new perspectives.

 

A few considerations are as below, as SRE capabilities mature, the governance model will evolve with more talent sitting in the spokes, meaning more work completed by the business sectors & the hub acting as a champion available when needed.

 

 

The SRE HUB exists to enable self-service model for the spokes. Typically built using the in-source model that builds embedded governance that is fit for purpose, the cross-pollination from spokes is key to following the product-based approach by the HUB.

 

The Evolution of the Mainframe

 

Mainframe and its evolution with Cloud Computing

The key attributes associated with mainframe computing are high resilience, high manageability, and scalability. Despite the momentum driving public cloud adoption, there remain workloads that cannot easily be migrated to the public cloud. Whether it is deemed too risky to migrate or reworking legacy code is cost-prohibitive, mainframe computing remains an integral part of IT ecosystem. There is a growing demand for reworking some mainframe workloads to run cloud natively on cloud infrastructure. But the risks associated with this often mean the core back-end mainframe system remains untouched in many organizations. APIs are used to provide external connectivity in order to enable enterprise developers to build modern functionality, combining the best the public cloud can offer with reliable transaction processing embodied in the mainframe.

Over the last few years, Cloud computing has evolved to the point where it is now promising the same level of scalability, flexibility, and operational efficiency that mainframe systems have long provided. In fact, in terms of scalability, it exceeds mainframe scalability. With scalability, throughput, operational efficiency, and arguably even resilience and failover, the cloud has arguably caught up with the mainframe of the 1990s or early 2000s. It is fair to say that cloud providers have made great strides in security and privacy, but, the mainframe is still recognized as the gold standard, with security baked into every layer in the systems stack.

The mainframe ecosystem and the z/OS operating system have evolved too and IBM has introduced specialty processors to run Linux workloads and support encryption, greatly increasing the flexibility of mainframe systems. Cloud providers offer support for specialist workloads for non-x86 hardware, such as graphics processing units (GPUs) for machine learning and AI. But the introduction of the latest addition to the z-series mainframe family, the z16, offers what IBM claims is the gold standard for highly secured transaction processing.

The mainframe environment is getting bigger with announcements such as those made at the recent launch of the IBM z16. These include quantum-safe cryptography to protect against the development of Quantum computers able to decrypt current encryption standards, on-chip AI acceleration to boost ML and AI execution and flexible capacity combined with on-demand workload transfer across multiple locations to further reduce the chance of service disruption.

On workload optimization, the two environments are developing in different ways. For example, the mainframe strives to deliver a consistent environment that can handle a wide range of workloads but is managed through the same set of frameworks and tools. The cloud, on the other hand, allows you to spin up dedicated specialized environments, e.g. for AI or analytics. Also, IBM Cloud’s ambition to make "mainframe as a service" available from its IBM Cloud and available across data centers, brings the mainframe capabilities closer to cloud-native offerings.

The modern mainframe, particularly LinuxOne version and the new Z16, it's pretty clear any claims of the mainframe being out of date or legacy stem from a fundamental lack of awareness. Indeed, the mainframe has continued to lead the way in many critical areas, delivering IT cost-effectively, and is far away from becoming obsolete.

 

DevOps, DevSecOps, and now NoOps, GitOps, BizDevOps, AIOps... what are these

As DevOps becomes more popular and continues to evolve, more variations are appearing There has always been DevSecOps, and now there is DevSecTestOps and DevSecTestMonOps, and so on…

however, this does not make any sense as DevOps integrates and encompasses Security, Monitoring, Observability and Test Automation tenets already. DevOps without Security is meaningless.

What is  BizDevOps? NoOps? DataOps? GitOps? What other terms have emerged and what do they mean? 

GitOps is an operational framework that takes DevOps best practices used for application development such as version control, collaboration, compliance, and CI/CD, and applies them to infrastructure automation 

BizDevOps is an agile software development methodology that encourages greater communication and collaboration among business, development, and operations teams throughout the software development lifecycle. 

NoOps is the idea that the software environment can be so completely automated that there's no need for an operations team to manage it 

DataOps is a collaborative data management practice focused on improving the communication, integration, and automation of data flows between data managers and data consumers across an organization. This includes an integrated approach to data ingestion flows to data engineering and data processing methods further leading to meaningful data analytics. Finally it's very gratifying that DevOps has been considered the pioneer for and a representation of a framework that breaks silos and fosters a collaborative culture

AIOps combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination

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Cloud Services - Get the Edge out of it post the Pandemic

As we head into 2022, we continue to feel the human toll of the global pandemic, but we already know it has been a watershed period in which attitudes and norms have permanently shifted — in our everyday lives and at work. Businesses have also changed. For many organizations, the pandemic has catalyzed digital business initiatives as we adapt to the demands of the new talent war, customer demand, who were forced into new digital options. B2B purchasers are happy to buy digitally, without a sales representative; B2C consumers are buying off social media platforms; Employees are physically distributed and communicating asynchronously; IT infrastructures must securing the “anytime, anyway, anywhere” way in which we’re operating; But to this age, we have seen customers esp. Government entities ask for on-prem solutions as the cloud is still perceived to be external and unsecure. There are still concerns on data privacy and a comfort that own data centre hosted applications can be hugged and secured with more controls. The “time to market” lag of an on-prem deployment (given the current supply chain issues due to the Pandemic) over a Cloud born deployment is expected to be anywhere between 3 – 6 months, and the pay as you model may allow your CAPEX project expenses for a medium web/mobile application to be reduced by 30 to 35% of overall project budget. A simple web and mobile deployment architecture for once of the CSPs is attached. More or less the same advantages can be met with other mature CSPs as they have equivalent Cloud services for web/mobile deployment.

Metaverse - from Employee Meetings to Manufacturing Line Efficiencies; from Digital Twins to Avatars.

Metaverse is a massive topic at present and is disruptive in bringing the physical and digital worlds together to create new sources of Business value. But this is not VR alone, or XR or AR or MR or NFTs or EMG gesture control or BCI (brain computing interface), or Digital Twins alone. Its a combination of things and it is the layer of digital content that connects the virtual 3D world with the real world, that can be accessible from VR headsets, AR/MR headsets, mobile phones, laptops and desktops. Of course, for highly immersive experiences, it is ideal to have a visual optical experience and hence a huge amount of research is also being done by the Tech Titans (like Google and Facebook) on optical technologies - how do you build the thinnest and the most fashionable eyewear and EMG handwear that will allow you the "Beyond experience" The transformational use cases are still evolving, and true to the term META which means BEYOND, the topic is constantly evolving, growing massively. What is estimated about the Metaverse growth, is as it is about People being the centre of Technology more than anything else, the growth will be what history may not have witnessed before, and with 5G bandwidth enablement, expected to touch 5B users and have an impact of around 10 Trillion USD by 2030, the penetration currently is less than 30%. A few use cases that we can see already being used are: 1) Effective onboarding of employees when remote, and when large scale growth reducing inefficiencies, time and cost, build deeper connections with new hires. The efficiencies, the immersiveness and the impact the Metaverse platform has had on employees is proven by some companies already. 2) Creating Digital Twins of physical spaces, meeting rooms, offices that would allow you to view and take vantage decisions that were hitherto not possible. 3) Employee collaboration with digital avatars moving onto common virtual spaces that are digital twins of the conference room of your office, or any other place you want all the avatars to meet in an immersive experience. 4) Training and Learning experiences in a Digital twin environment (for example a digital twin of shop floor or on the interior of the Aircraft) takes learning and retention of knowledge to a whole new level of experience. 5) Having a digital twin of Manufacturing lines allows efficiencies, to identify issues in the shopfloor, or supplier chain issues resulting in a pileup. 6) Interaction with customers can be done at a completely new level new-gen Business, for example a car manufacturer through digital assets (NFT) can have the complete history of the car tracked, and when the car is being transferred to the next customer can have a share of the revenue. The use cases are just endless. 7) NFT based economy from digital real estates to Art collections is opening a completely new unforeseen world of opportunities. 8) Having digital twins of real estate properties, and virtual visiting of places with an immersive collaborative experience where people can interact will take the business-client relationship to a positively higher level. The advantages are visible and significant, if organisations can start small, start experimenting and when the tip of the transformation happens such organisations will be ahead of the curve from a strategic, technology and business know-how point of view. Underlying Technologies are data and AI based technologies, data modelling, data Engineering, AI/ML/DL, computer vision, AR/VR/MR, holography, NLP, Blockchain and data science/Metaverse platforms such as Microsoft Mesh & Space, Unity3D, Unreal Engine, Amazon Sumerian, SparkAR, Cybernetics among others. The Metaverse is indeed a place of infinite possibilities.