2019 Predictions from SIOS Technology

Jerry Melnick

The following are 2019 predictions for the cloud, high availability (HA) and disaster recovery (DR).

ADVANCES IN CLOUD TECHNOLOGY

Advances in Technology Will Make the Cloud Substantially More Suitable for Critical Applications

Not surprisingly, organizations will expand the use of cloud services in 2019 for both existing and new applications, further accelerating the migration of workloads from the datacenter to the cloud. With IT staff now becoming more comfortable in the cloud, their concerns about high availability (HA) and disaster recovery (DR) will also begin to ease. This change is significant because the workload migration will increasingly include mission-critical applications.

Companies have long relied on purpose-built HA failover clustering technology in their datacenters to protect their most critical enterprise applications. These third-party failover clustering solutions will further evolve to adapt and optimize operations for the cloud, making the cloud more suitable for critical enterprise applications.

At the same time cloud service providers will continue to advance their basic availability capabilities to meet the needs of a broad range of applications, many of which have lesser demands than for full HA, but still need basic DR assurances. With the evolution of both third-party clustering and nascent cloud availability capabilities, along with ready access to cloud DR capabilities, migrations from on-premises to cloud will accelerate.

COST-EFFECTIVE HA AND DR

Dynamic Utilization Will Make HA and DR More Cost-effective for More Applications, Further Driving Migration to the Cloud

Economies of scale and on-demand provisioning in the cloud are nothing new. What will be new in the cloud is the ability to dynamically configure its virtually unlimited resources spread among multiple availability zones and geographical regions. And this on-demand high-availability will make the cloud an even more cost-effective platform for critical applications.

High availability requires redundancy, with standby resources that are provisioned and ready to run, to enable rapid recovery under all possible failure scenarios. These standby resources all sit idle unless and until called into service during a failover from the primary. The increasing sophistication of fluid cloud resources across zones and regions connected via high-quality internetworking now enables standby resources to be allocated only when needed, making HA and DR far more affordable.

CLOUD FOR SAP

The Cloud Will Become a Preferred Platform for SAP Deployments

SAP is the undisputed leader in supply chain management, making its SAP and SAP S4/HANA-based applications the lifeblood of organizations around the world. Given its mission-critical nature, IT departments have historically chosen to implement SAP in enterprise datacenters, where the staff enjoys full control over the environment.

As the platforms offered by cloud service providers continue to mature, their ability to host SAP applications will become commercially viable and, therefore, strategically important. For CSPs, SAP hosting will be a way to secure long-term engagements with enterprise customers. For the enterprise, "SAP-as-a-Service" will be a way to take full advantage of the enormous economies of scale in the cloud, while also enabling IT to focus on service delivery rather than infrastructure management—all without sacrificing performance or availability.

QUICK-START TEMPLATES

Cloud "Quick-start" Templates Will Become the Standard for Complex Software and Service Deployments

The statement "some assembly required" has always been the case when implementing new applications or provisioning new services, whether in a private, public or hybrid cloud environment. Beginning in 2019, cloud service providers will simplify provisioning with more widespread adoption of quick-start templates. These templates are wizard-based interfaces that employ automated scripts to dynamically provision, configure and orchestrate the resources and services needed to run specific applications.

Among their key benefits are reduced training requirements, improved speed and accuracy, and the ability to minimize or even eliminate human error as a major source of problems for DevOps. Their use will substantially decrease the time and effort it takes for IT staff to setup, test and deploy dependable HA and DR configurations. The resulting turnkey deployments can be expected to become a new best practice for even the most critical of applications.

ADVANCED ANALYTICS AND AI

Advanced Analytics and Artificial Intelligence Will Be Everywhere and in Everything, Including Infrastructure Operations

Analytics and AI will continue becoming more highly focused and purpose-built for specific problems, and these capabilities will increasingly be embedded in cloud platforms and management tools.

AI-driven infrastructure tools, for example, are now being used to analyze input from a myriad of monitoring and management tools. Many of these AI tools have endeavored to solve broad problems across the IT spectrum. In 2019 these will begin to evolve to become substantially more focused on the most critical problems — both the routine and complex — encountered by IT staff. This much-anticipated capability will simplify IT operations, improve infrastructure and application robustness, and lower overall costs.

Along with this trend, AI and analytics will naturally become embedded in HA and DR solutions, as well as CSP offerings, to enhance the robustness of their operations. With the ability to quickly, automatically and accurately understand issues and diagnose problems across complex configurations, the reliability, and thus the availability, of critical application services delivered from the cloud will vastly improve.

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2019 Predictions from SIOS Technology

Jerry Melnick

The following are 2019 predictions for the cloud, high availability (HA) and disaster recovery (DR).

ADVANCES IN CLOUD TECHNOLOGY

Advances in Technology Will Make the Cloud Substantially More Suitable for Critical Applications

Not surprisingly, organizations will expand the use of cloud services in 2019 for both existing and new applications, further accelerating the migration of workloads from the datacenter to the cloud. With IT staff now becoming more comfortable in the cloud, their concerns about high availability (HA) and disaster recovery (DR) will also begin to ease. This change is significant because the workload migration will increasingly include mission-critical applications.

Companies have long relied on purpose-built HA failover clustering technology in their datacenters to protect their most critical enterprise applications. These third-party failover clustering solutions will further evolve to adapt and optimize operations for the cloud, making the cloud more suitable for critical enterprise applications.

At the same time cloud service providers will continue to advance their basic availability capabilities to meet the needs of a broad range of applications, many of which have lesser demands than for full HA, but still need basic DR assurances. With the evolution of both third-party clustering and nascent cloud availability capabilities, along with ready access to cloud DR capabilities, migrations from on-premises to cloud will accelerate.

COST-EFFECTIVE HA AND DR

Dynamic Utilization Will Make HA and DR More Cost-effective for More Applications, Further Driving Migration to the Cloud

Economies of scale and on-demand provisioning in the cloud are nothing new. What will be new in the cloud is the ability to dynamically configure its virtually unlimited resources spread among multiple availability zones and geographical regions. And this on-demand high-availability will make the cloud an even more cost-effective platform for critical applications.

High availability requires redundancy, with standby resources that are provisioned and ready to run, to enable rapid recovery under all possible failure scenarios. These standby resources all sit idle unless and until called into service during a failover from the primary. The increasing sophistication of fluid cloud resources across zones and regions connected via high-quality internetworking now enables standby resources to be allocated only when needed, making HA and DR far more affordable.

CLOUD FOR SAP

The Cloud Will Become a Preferred Platform for SAP Deployments

SAP is the undisputed leader in supply chain management, making its SAP and SAP S4/HANA-based applications the lifeblood of organizations around the world. Given its mission-critical nature, IT departments have historically chosen to implement SAP in enterprise datacenters, where the staff enjoys full control over the environment.

As the platforms offered by cloud service providers continue to mature, their ability to host SAP applications will become commercially viable and, therefore, strategically important. For CSPs, SAP hosting will be a way to secure long-term engagements with enterprise customers. For the enterprise, "SAP-as-a-Service" will be a way to take full advantage of the enormous economies of scale in the cloud, while also enabling IT to focus on service delivery rather than infrastructure management—all without sacrificing performance or availability.

QUICK-START TEMPLATES

Cloud "Quick-start" Templates Will Become the Standard for Complex Software and Service Deployments

The statement "some assembly required" has always been the case when implementing new applications or provisioning new services, whether in a private, public or hybrid cloud environment. Beginning in 2019, cloud service providers will simplify provisioning with more widespread adoption of quick-start templates. These templates are wizard-based interfaces that employ automated scripts to dynamically provision, configure and orchestrate the resources and services needed to run specific applications.

Among their key benefits are reduced training requirements, improved speed and accuracy, and the ability to minimize or even eliminate human error as a major source of problems for DevOps. Their use will substantially decrease the time and effort it takes for IT staff to setup, test and deploy dependable HA and DR configurations. The resulting turnkey deployments can be expected to become a new best practice for even the most critical of applications.

ADVANCED ANALYTICS AND AI

Advanced Analytics and Artificial Intelligence Will Be Everywhere and in Everything, Including Infrastructure Operations

Analytics and AI will continue becoming more highly focused and purpose-built for specific problems, and these capabilities will increasingly be embedded in cloud platforms and management tools.

AI-driven infrastructure tools, for example, are now being used to analyze input from a myriad of monitoring and management tools. Many of these AI tools have endeavored to solve broad problems across the IT spectrum. In 2019 these will begin to evolve to become substantially more focused on the most critical problems — both the routine and complex — encountered by IT staff. This much-anticipated capability will simplify IT operations, improve infrastructure and application robustness, and lower overall costs.

Along with this trend, AI and analytics will naturally become embedded in HA and DR solutions, as well as CSP offerings, to enhance the robustness of their operations. With the ability to quickly, automatically and accurately understand issues and diagnose problems across complex configurations, the reliability, and thus the availability, of critical application services delivered from the cloud will vastly improve.

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AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Exploring AI Observability – Part 4: Challenges

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Exploring AI Observability – Part 3: The Current State of AI Observability

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

Exploring AI Observability – Part 2: Traditional vs. AI Observability

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

Exploring AI Observability – Part 1: Why It Matters

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

AgenticOps Scaling Quickly in the Enterprise

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

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AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

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Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

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For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

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Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...