Charlotte is a Senior Analyst for Application Platforms at Current Analysis. She covers the technologies that provide the infrastructure necessary to build and run enterprise applications and services. She analyzes the software, services and professional services necessary to integrate disparate systems, create cross-business and cross-technology communications, deliver rich, collaborative applications, and build software that is transparent, optimized and reusable.
Robotic process automation (RPA) represents the key component of intelligent automation solutions which will support DevOps and app modernization efforts in the coming year.
Emerging factors including process mining/task mining, low-code app platforms, API integration, test automation, intelligent document processing, and attended automation capabilities promise to fast-track the technology into enterprises’ digitization strategies.
The pandemic brought to the forefront the importance of intelligent automation and robotics advancements for addressing a changing global workforce, turning traditional business processes into workflow automations to vastly improve the customer experience. The result will be a new workforce represented by RPA’s replacement of repetitive and mundane jobs, alongside new high-touch, high-productivity opportunities fulfilled by humans. Robotics’ core heritage has always been RPA, but additional factors including process mining/task mining, low-code app platforms, API integration, test automation, intelligent document processing, and attended automation capabilities are coming to light and promise to fast-track the technology into enterprises’ digitization strategies. Continue reading “Robotics to Play Mega Role in Automation and Process Mining”→
The Open Source Security Foundation (OpenSSF), a new group focused on software security supply chain problems, added $10 million in vendor funding.
Google Cloud recently joined the FinOps Foundation, representing the first major cloud provider to commit.
The recent KubeCon 2021 conference garnered much attention not only for its hybrid format (virtual/in-person), but also for its critical role in helping facilitate interaction between customers (primarily developer and IT operations teams) and vendors as enterprises navigate the unchartered waters of digital and business transformations. A number of important topics and themes raised during the conference were highly relevant to DevOps teams tasked with overseeing an increasingly diverse and distributed IT portfolio. Continue reading “Key Takeaways from KubeCon: Deeper Focus on FinOps, GitOps”→
Salesforce’s Slack integration into high-productivity platforms eases IT’s ALM demands.
Microsoft initiated collaboration integration with developer platforms via Teams and Power Platforms.
Why have collaboration tools suddenly become an indispensable piece of the DevOps toolbox? Well, some might say the advent of the global pandemic and the rise of low-code’s prominence after being injected with AI have created the perfect storm for shoring up the next wave in app modernization. Continue reading “Collaboration Finds a Seat at the DevOps Table”→
Summary Bullets: • Mendix’s data integration technology now supports app dev around business events • Appian focused on support for composite data synchronization and data integration
Those pure-plays involved in the highly competitive low-code wars focused heavily on data integration strengths during the past week. Mendix and Appian, respectively, made significant updates to their flagship low-code automation platforms, focused primarily on providing developers with more AI/ML access and innovative data integration capabilities.
Building on its model-driven development strengths, Mendix’s platform updates during its annual conference last week focused on bringing agility to app development through automation, AI, and pre-built templates. At the heart of Mendix’s portfolio is its integration management platform Data Hub, which now lets developers display business events (such as purchases or help desk tickets) and build automated responses when triggered. Emerging intelligent workflow automation is a top priority among operations teams.
Appian continues to invest in its low-code and intelligent automation capabilities, acquiring highly relevant innovators including Novayre last year and recently process mining provider Lana Labs. Stemming from its BPM heritage, Appian differentiates from rivals through its focus on low-code/no-code automation addressing complex workflows through a combination of BPM, API integration, decision rules, RPA, AI, and case management capabilities. Its latest announcements focus further on its support for composite data synchronization and data integration, although the announcement was short on details including Lana Labs integrations.
The fast-moving low-code app development space is highly competitive, and as such rivals are quickly consolidating new innovations into broader solutions in an effort to improve their application lifecycle management (ALM) standing to better address DevOps models. Low-code enabled AI and automation innovations coupled with the cloud have created a culture of data ubiquity where data from virtually any source can be accessed and integrated into modern apps.
Low-code platforms have demonstrated an increasingly important role in enterprises’ application modernization process for the past few years, catering to both professional developers and non-coders in the role of business users. The advent of AI helped low-code platforms flourish over the past couple years, improving their ability to support the development and deployment of mission critical apps. Low-code platforms are consolidating further to include automation technologies, largely through robotic process automation (RPA) as a key component for shoring up DevOps models. Automation of backend data integration supports operations’ need to digitize workflows and business processes to support application lifecycle management (ALM) and continuous integration, continuous delivery (CICD). ML models will eventually be incorporated into solutions, building on next best action models to more quickly react to event-driven architectures.
GlobalData has just updated its Low-Code Competitive Landscape Assessment (CLA) for further vendor comparisons and low-code trends and drivers, please click here.
• Over the next six to 12 months, the observability market segment will evolve to include more comprehensive solutions which provide application-level observability data alongside systems-level data, delivered through pre-set parameters
• The future of observability is ML-powered predictive and prescriptive analytics to enable proactive responses that prevent problematic incidents
Accelerated digital business transformations are steering operations teams towards new observability stacks to oversee an increasingly diverse and distributed IT portfolio. Ops teams are overwhelmed with the move from monolithic apps to microservices where various service components within a single app must be secured and managed. New monitoring tools are emerging to help developers collaborate under DevOps models and gain automated visibility into the impact of modern coding on underlying systems. Observability solutions will shorten the lengthy feedback cycle involved before committing apps to code, enhancing the quality of apps moving through the pipeline.
• ServiceNow’s acquisition of modern database vendor Swarm64 combined with Lightstep’s modern monitoring platform aligns nicely with ServiceNow’s observability strategy.
• Under increased pressure to accelerate digitization of company apps and systems, integrated observability technologies (as a component of automation solutions) will play a significant role in accelerating app modernization in the next six to 12 months.
Last week saw more jostling among players involved in the hotly contested intelligent automation space, with workflow automation leader ServiceNow continuing its technology buying spree to reinforce its DevOps arsenal.
ServiceNow announced plans last week to acquire hybrid database vendor Swarm64 to help ease management of large volumes of data transactions via advanced analytics. The move comes on the heels of its acquisition of Lightstep, a modern monitoring platform which aligns nicely with ServiceNow’s observability strategy. ServiceNow has become a growing competitive threat in the automation and observability space, stemming from enhancements to its Now Platform under an initiative the company calls insight-guided workflows.
• Modernizing workflow processes has become a complex endeavor as a result of increased data sources and volumes
• Automation, when applied to IT, provides capabilities that bring insights and diagnostics into various backend systems
AI-injected automation has become the power source for digitizing companies in a pandemic era, ensuring resilience, agility, and efficiency for modern, distributed apps. Modernizing workflow processes has become a complex endeavor as a result of increased data sources and volumes, heightening the need for comprehensive data management, integration, and security strategies. Automation, when applied to IT however, provides capabilities that bring insights and diagnostics into various backend systems, including pre-determined automation of problem remediation and policy controls.