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Unveiling the Latest Edition of CIOInsights: Exploring IBM Partner Innovations We are thrilled to announce the upcoming release of CIOInsights, dedicated to the cutting-edge innovations within the IBM Partner ecosystem. This special edition offers an exclusive look into some of the most influential IBM partners driving digital transformation across industries, providing CIOs and IT leaders with invaluable insights. Cover Story: Prolifics - Transforming Enterprises Through IBM Solutions Leading this edition is Prolifics, featured as the cover story for their outstanding work in digital transformation. As a key IBM partner, Prolifics helps businesses harness data, automation, and cloud technologies to accelerate growth. Learn how they are shaping the future of enterprise IT and solving complex business challenges. Spotlight on Leading IBM Partners: This edition also highlights other pivotal IBM partners, including: Celerity Limited: Empowering organizations to navigate digital change with IBM’s innovative solutions. CoEnterprise: Driving operational efficiency and unlocking data potential through IBM technology. STORServer, Inc.: Leading the way in data protection, backup, and disaster recovery. Recovery Point Systems: Specializing in IBM-powered business continuity and disaster recovery services. Technologent: Modernizing IT infrastructures with IBM’s advanced platforms for competitive advantage. Expert Articles and Industry Insights In addition to partner features, this edition is filled with articles and thought leadership from the IBM field. Readers can expect deep dives into the latest trends, including AI, hybrid cloud, and automation, with actionable insights that technology leaders can apply to their own organizations. From exclusive interviews to practical strategies, this issue brings together perspectives from across the IBM ecosystem. Your Gateway to Innovation This edition of CIOInsights offers a comprehensive look at how IBM’s leading partners are enabling businesses to innovate, grow, and stay resilient in today’s fast-paced digital landscape. Whether you’re an IT professional, business leader, or technology enthusiast, this is your opportunity to learn from the best. Read Now - https://lnkd.in/gqMPz8DR

Your deployments should be fully automated No human intervention allowed as humans will eventually make mistakes. Deployments should also be executable, over and over again. Ideally in an incremental fashion. But also from scratch if needed in case of a disaster (mind the data). So how do you do that? First use 'infrastructure as code' to provision any shared infrastructure such as networking, security, communication or storage infrastructure. Ideally your infrastructure as code allows composition in its own right. We use Azure Bicep, which has support to load bicep modules from the azure container registry. This allows teams to maintain their own templates for e.g their subnet, while the network is still provisioned as a whole. The same goes for their storage, security and communication needs. Once the infrastructure is in place each composed host can be provisioned independently through its own deployment orchestration pipeline. Teams are free to choose the orchestration technology of their choice. Kubernetes, container apps, app services, service fabric, or whatever else they feel most comfortable with. Finally there is the data. Make a habit from automatically restoring, migrating and rebuilding your data on a regular basis Data on the inside: Prefer stable schemas, such as an event source, maintain backups and restore as is. If any new data needs to be added, append it. Data on the outside: no need to maintain backups. You should be able to rebuild this data from the original source of truth at all time. Rebuild it from scratch into a new version for every deployment containing schema changes.

Common Migration challenges: Compatibility Issues: Ensuring that applications, databases, and services are compatible with Azure can be a significant challenge. This may require code refactoring or adjustments to make them work seamlessly in the cloud. Data Migration: Moving large volumes of data to Azure can be complex and time-consuming. Ensuring data integrity, minimal downtime, and efficient transfer is a challenge. Downtime Minimization: Reducing downtime during migration is critical for business continuity. Achieving zero or minimal downtime can be a challenge, especially for complex applications. Security and Compliance: Maintaining security and compliance standards during migration is vital. Ensuring data protection, identity management, and compliance with regulations can be challenging. Cost Management: Azure costs can escalate if not properly managed. Controlling and optimizing costs during and after migration is a challenge. Skill Gaps: Organizations may lack the necessary Azure expertise. Training or hiring skilled professionals is often required. Legacy Systems: Migrating legacy systems can be challenging due to their outdated architecture and dependencies. Testing and Validation: Comprehensive testing to ensure that applications work correctly in Azure is crucial. Validation and troubleshooting can be time-consuming. Change Management: Preparing teams and stakeholders for the changes that come with cloud migration is essential. Resistance to change can be a challenge. Resource Scaling: Determining the right amount of resources to allocate in Azure can be tricky. Overprovisioning or underprovisioning can lead to performance issues or unnecessary costs. Best practice for Migration: Plan carefully:Before you begin migrating applications or data, be sure to develop a detailed migration plan. This plan will identify the applications and data you need to migrate, the migration strategy for each application and data set, and the migration timeline. Choose the right migration strategy:There are several different migration strategies, such as lift and shift, restructuring, restructuring, and acquisitions. Choose the migration strategy that best suits your specific needs and requirements. Use Azure tools and services:Azure offers several tools and services to help you migrate, such as Azure Migrate, Azure Site Recovery, and Azure ExpressRoute. Use these tools and services to make your move easier and more efficient. Check your migration:Before moving to Azure, be sure to test your migrated applications and data in a staging environment. This will help you identify any potential problems and make any necessary adjustments to your travel plans. Monitor your migration:Monitor the move closely to ensure it goes smoothly. Monitoring should be done constantly to avoid any mishap.

As cloud virtualization and data management grow in complexity, several challenges arise that can hinder efficiency and security. Systech’s managed services are designed to tackle these problems effectively: 1. Data Security and Compliance Data breaches and non-compliance with regulations are major concerns. Systech ensures robust encryption, identity management, and compliance frameworks to protect sensitive information and meet regulatory requirements. 2. Resource Optimization Inefficient resource allocation can lead to high costs and underperformance. Systech’s managed services optimize resource utilization through advanced monitoring and automated scaling, ensuring cost-effectiveness and high performance. 3. Complex Infrastructure Management Managing a hybrid or multi-cloud environment can be complex and time-consuming. Systech provides seamless integration and centralized management, simplifying operations and reducing the burden on internal IT teams. 4. Downtime and Reliability Issues Unplanned downtimes can disrupt business operations. Systech ensures high availability and reliability with proactive monitoring, disaster recovery solutions, and regular maintenance to minimize downtime. 5. Data Integration and Accessibility Integrating data from various sources and ensuring its accessibility can be challenging. Systech’s managed services offer seamless data integration and ensure that data is easily accessible and usable across the organization. 6. Scalability Challenges Scalability issues can arise as data volumes grow. Systech leverages advanced technologies like Kubernetes and containerization to provide scalable solutions that grow with your business needs. 7. Performance Bottlenecks Performance issues can slow down applications and processes. Systech identifies and addresses performance bottlenecks through continuous monitoring and optimization, ensuring smooth and efficient operations. #DATA #ManagedServices #IT #Technology #futureproof

AI-Powered Service Models Speed Troubleshooting https://lnkd.in/gfTxqiYr If you manage a modern distributed IT environment, context is critical for troubleshooting and analyzing the business impact of production issues. But that context can be hard to acquire. You might have different teams and observability solutions managing the different layers that contribute to a business service, or different tools that generate useful telemetry data, such as metrics, events, logs, traces and topology, but they operate in silos. Maybe you don’t have a model of the connections in your environment. Or possibly all the knowledge about cause-and-effect relationships, actions and consequences is not documented but locked in someone’s institutional memory. To pinpoint the root cause of service issues accurately and quickly in complex environments, you need deep understanding of critical paths and dependency levels across the application, API and network layers. Highly performant graph databases, dynamic service modeling capabilities and causal AI can help you understand and model the cause-and-effect relationships between different applications, APIs and network and infrastructure layers. Modeling your service — building a visualization of services and the relationships between various system and infrastructure components — provides critical context for troubleshooting. A well-defined service gives you an end-to-end view to quickly identify an impacted node for faster root cause analysis. How Service Modeling Works Assuming you have a dynamic and reconciled graph database of your IT landscape where all types of ingested data (metrics, events, logs, traces, topology) are normalized, modeling your service involves the following steps: Identify end-user services that you want to model and add service details as inputs to the service modeling tool. An application performance monitoring (APM) tool can provide application-specific details about software components and their relationships across cloud, mainframe and container topologies. Infrastructure and network monitoring tools and scanning tools can detail the infrastructure’s connectivity to underlying virtual and physical devices, such as servers, databases, switches, routers, firewalls and load balancers. Use blueprints to dynamically traverse all layers to automatically connect the application topology to the hosts and network devices. Discovery and monitoring tools can provide service blueprints to simplify creating and maintaining dynamic service models. These service models support modern technologies like microservices, Kubernetes, cloud services, application performance tracking and mainframes to keep accurate tabs on all IT resources and relationships. Blueprints make it easy to express a simple rule that identifies all the elements of your service. You define the rule once and apply it to as many services as needed. Calculate the health score for a service. Understanding a service’s ...

🌐 Navigating the Challenges of Stateful Applications in Production 🌐 As enterprises increasingly adopt cloud-native architectures, managing stateful applications in production environments remains a significant challenge. According to a recent survey, over 60% of organizations struggle with maintaining high availability and data persistence for their stateful applications. Here are a few key issues that many organizations face: // Data Persistence and Availability: Ensuring data persistence and high availability in stateful applications can be complex. Traditional storage solutions often fall short in providing the reliability and performance needed for dynamic, containerized environments, leading to potential data loss and service disruptions. 📀 // Scalability Issues: Stateful applications require careful management of storage resources as they scale. Without automated and scalable storage solutions, organizations may struggle to efficiently scale their applications, resulting in bottlenecks and increased operational overhead. ⚖️ // Backup and Disaster Recovery: Implementing robust backup and disaster recovery strategies for stateful applications is critical but challenging. Enterprises need solutions that offer seamless, automated backup and recovery processes to minimize downtime and ensure business continuity. 🩹 Come and talk to us, we know how to solve these bissues and have enterprises who can testify! 🗣️ HighPoint & Portworx by Pure Storage & Ethos Technology #StatefulApplications #DataManagement #CloudNative #ProductionChallenges #TechSolutions #TechChallenges #DevOps #TechEducation

The era of enterprise ‘compute + connectivity’ has arrived. Essentially all applications operate in some form of hybrid environment - connecting to multiple devices and clouds… As such, automating the network services and IT that connect them together is a strategic imperative - it allows for faster deployment times continuous Bandwidth and performance optimization and higher confidence in SLA’s and QoS! To achieve best in class marketplace agility and productivity - you must modernize your enterprise technology architecture… Think horizontal: building up from workload optimized infrastructure * a standardized K8 platform layer * open data lakehouse * zero trust security * extreme automation * and AI wrapped with governance. Andrew Coward Bill Lobig Kareem Yusuf Ph.D Dinesh Nirmal Marc Peters Mathews Thomas Linda Oberhoff Dawn Babb Gina Holmes Peter Sarbach Tony Aguirre Werner Klemm

How can you anticipate potential technical hurdles or challenges that might arise as you scale? Anticipating potential technical hurdles or challenges as you scale is crucial for maintaining the stability, performance, and efficiency of your systems. Here are several strategies and considerations for identifying and preparing for these challenges: **1. Assess Current System Architecture Evaluate Scalability: Review your current system architecture to identify components that may become bottlenecks as the system scales. Look for single points of failure, limitations in performance, and constraints in the architecture. Modular Design: Ensure that your system is modular and can be scaled horizontally by adding more instances rather than vertically by upgrading existing components. **2. Analyze Performance Metrics Monitor Metrics: Continuously monitor performance metrics such as CPU usage, memory consumption, network bandwidth, and response times. This helps identify performance trends and potential bottlenecks. Stress Testing: Conduct stress tests to simulate high-load scenarios and identify how your system handles peak loads. This helps you understand the limits of your current infrastructure and plan for scaling. **3. Plan for Data Growth Database Scalability: Ensure that your database can handle increasing amounts of data. Consider database sharding, partitioning, and indexing strategies to manage large datasets. Data Consistency: Address issues related to data consistency and integrity as you scale, especially if using distributed databases or systems. **4. Design for Fault Tolerance and Redundancy High Availability: Implement high availability and redundancy strategies to minimize downtime and ensure continuous service. Use failover mechanisms, backup systems, and disaster recovery plans. **5. Evaluate Software and Tools Framework and Libraries: Ensure that the frameworks and libraries you use are designed to scale. Some tools may have limitations or performance issues at scale. **6. Optimize Resource Management Auto-Scaling: Implement auto-scaling mechanisms to dynamically adjust resources based on demand. This helps manage load efficiently and reduces costs. **7. Consider Security Implications Security Risks: Assess potential security risks that may arise as you scale, such as increased exposure to attacks or vulnerabilities due to a larger attack surface. Compliance: Ensure that scaling does not compromise compliance with regulatory requirements and data protection standards. **8. Plan for DevOps and CI/CD Deployment Pipelines: Develop robust CI/CD pipelines to automate the deployment process, ensuring that changes are tested and deployed smoothly as you scale.

𝗛𝗼𝘄 𝘁𝗼 𝗠𝗼𝘃𝗲 𝗼𝗻 𝗳𝗿𝗼𝗺 𝗟𝗲𝗴𝗮𝗰𝘆 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗗𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗻𝗴 𝗬𝗼𝘂𝗿 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 Migrating from a legacy system is a complex product engineering challenge. Here's a structured approach to ensure a smooth transition: 𝟭. 𝗔𝘀𝘀𝗲𝘀𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗗𝗲𝗯𝘁 Evaluate your legacy system to identify risks and opportunities involved in the migration process. -Understand which parts of your legacy system are most essential. -Assess potential risks and create mitigation strategies. 𝟮. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗮 𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗣𝗹𝗮𝗻 Develop a comprehensive plan that addresses all aspects of the migration. -Focus on critical functionalities to ensure business continuity. -Plan for potential challenges and how to overcome them. 𝟯. 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗿𝗻 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 Utilize cloud-based infrastructure and modern software technologies. -Move to a scalable, flexible cloud infrastructure. -Adopt microservices and other modern architectural patterns. 𝟰. 𝗘𝗻𝘀𝘂𝗿𝗲 𝗖𝗼𝗺𝗽𝗮𝘁𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗦𝗺𝗼𝗼𝘁𝗵 𝗗𝗮𝘁𝗮 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻 Maintain compatibility with existing technologies and ensure a seamless data transition. -Use robust data migration tools to ensure data accuracy and integrity. -Ensure new systems work well with existing applications. 𝟱. 𝗠𝗮𝗶𝗻𝘁𝗮𝗶𝗻 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗼𝗿𝘆 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 Ensure that your new systems comply with all relevant regulations and standards. -Regularly audit new systems for compliance. -Implement strong security measures to protect data. 𝟲. 𝗦𝗮𝗳𝗲𝗴𝘂𝗮𝗿𝗱 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 Protect the reliability and security of your new systems during the transition. -Perform extensive testing to ensure system reliability. -Use advanced security protocols to protect sensitive information. 𝟳. 𝗠𝗶𝗻𝗶𝗺𝗶𝘇𝗲 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗗𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗼𝗻 Ensure minimal disruption to business operations during the migration process. -Implement changes in phases to minimize impact. -Keep all stakeholders informed throughout the process. #LegacySystem #AppModernization #DigitalTransformation #CloudInfrastructure #ProductEngineering #BusinessGrowth

ARCHITECUTRE QUALITY ATTRIBUTES Any technical solution needs to have at least some of these attributes irrespective of which technologies, tools it requires for implementation or which business features will it provide. Teams and organizations have to decide which attributes are more important then others as having more focus on a specific quality attribute can effect another attribute Availability Efficiency Integrity Interoperability Maintainability Performance Portability Reliability Reusability Robustness Safety Scalability Security Usability Verifiability Operations If performance is valued more then security will be effected as systems will have more focus on speed, efficiency, scalability, caching and automatically security will be compromised. Similarly, if focus is more on scalability then costs will increase due to redundancy of caches, messaging queues, load balancers, servers, systems, containers and databases Each attribute provides its unique value to the solution that is designed. Its impossible to achieve 100% in any attribute. Availability for example can be 99.9999 percent at max but no technology or solution in the world can promise it to be 100% every time in any scenario. Commonly, organizations when architecting software solutions and technical products focus more on availability, scalability, security, operational quality and performance. SECURITY, SAFETY Security is achieved by firewalls, encryption, decryption, transfer protocols, vulnerability management, network safety, authentication, authorization and session management PERFORMANCE, SPEED Performance is achieved by caching, memory improvements, data schema (NoSQL), network calls reduction, more servers, containers and microservices SCALABILITY, REDUNDENCY Scalability is provided by having multiple instances of resources such as microservices, micro frontends, servers, cache memories, load balancers, app gateways, data platforms, containers & storage systems AVAILABILITY, RESILIENCY Similarly availability is provided by disaster recovery, monitoring, observability, deployment patterns, various testing patterns, data replication and system resiliency techniques OPERATIONAL PROCESS Operational costs are improved by governance, management, operations and investment pipelines (DevOps, Agile, Scrum, SAFe, ART, ITIL, ITSM). INTEROPERABILITY Its provided by adding data transfer protocols such as GraphQL, REST, SOAP for communication between various services, modules within a single application (microservices, micro frontends) or among various systems. Due to the nature of distributed products (various technologies) interoperability is highly valued today USABILITY Today systems are extremely complex. Having system easily understandable and navigable is highly valuable attribute otherwise business can loose money or if its internal product then users would need more time to learn how to use it