A leading provider of personal, commercial property, casualty insurance, and long-term retirement savings products in the US faced challenges in managing their long-tail apps. They struggled to build apps independently of internal IT intervention, which required additional operating investments. The major challenges included high development and support costs imposed by IT for non-critical apps and the need to create a minimal IT dependency channel for infrastructure provisioning, support, data access, and app maintenance. The internal IT team wanted to focus on core business applications and spend minimal effort on maintaining long-tail apps.

Companies find it difficult to change the packaged applications they get from ISVs. No matter how good a software package is, invariably it will have to be changed in some way to fit the way the company works or its particular market or some specific process that gives it a competitive advantage. Every company is different; even routine business processes common to most businesses, such as answering customer questions, responding to email inquiries or processing online sales, differ for every organization. The issue of changing software becomes particularly acute when the ISV’s software addresses interaction with customers and other key stakeholders. In such customer-facing situations, organizations want the software to exactly match their business processes. And to complicate matters, a process may be slightly different even for different groups within the same company. In that case, no single change or set of changes works for everybody. That was the situation KANA faced. ISVs like KANA need visual configuration tools like WaveMaker built into their products to simplify the change process, both for the client and for the ISV. Without something like WaveMaker, ISVs that want to do the right thing for their clients in terms of ease of change often find themselves scrambling to support multiple versions of the product. This dramatically increases the cost of development, product management and support.

One of the most important challenges that the WaveMaker team had to overcome was the stringent security requirements of the bank’s internal IT team. As a rule, all applications in the IT department went through rigorous vulnerability and penetration tests under rigid constraints before deployment. Additionally, every application had to be certified for US compliance and regulations. Also, WaveMaker had to conform to the client’s internal infrastructure. Security restrictions prevented internet connectivity for internal systems. This posed a major challenge in releasing updates and dependencies of the WaveMaker platform.

Modernization on top of legacy technologies was cumbersome and involved high latency, existing systems did not support open-source technologies. Existing technologies could not interface natively with other internal and essential systems like SAML and LDAP. Some existing technologies were expensive and their licensing model was not cost-effective. Delay in go-to-market with application updates arising from Government policies and rules that are subject to change over time.

The global pizza delivery chain initially used Voldemort containers for custom replication between datacenters. Although the performance was acceptable, replication was unreliable, affecting customer order history and profile data. The early adoption of Voldemort made the upgrade path difficult, and there was no tangible support available. This led the development team to explore more modern storage architectures. They experimented with SQL Server and Memcached, but neither achieved the required performance results. Concurrently, a social media project required de-duplication of data from multiple Twitter feeds, leading them to Hazelcast IMDG as a microservices alternative to Voldemort. The Twitter project team realized they needed a solution to coordinate data between multiple nodes, and Hazelcast IMDG's potential as a replacement became evident when combined with SQL Server, providing the necessary flexibility and tooling to meet performance goals.

Before Ellie Mae adopted Hazelcast, its Encompass application was suffering from two major problems: performance and scalability. Encompass could not function within the approved service level agreements due to the disk-based access methodology of its database vendor, resulting in high latencies and lower throughput. Attempts at caching frequently used data in the Encompass application’s memory with a homegrown caching solution failed due to data inconsistency across application nodes. This internal solution was too burdensome to maintain and did not guarantee high availability, resulting in failed SLAs. Scalability was another major challenge, as Ellie Mae was expecting its business to grow by 25% to 30% every year, and its current application memory setup was not scalable, potentially resulting in significant losses.

Fluidra was already reviewing their e-commerce platform as they recognized the need for modernization to future-proof their business. They also had existing latency and network bandwidth issues due to their ERP-centric architecture. The tight coupling with their ERP systems meant that they were limited in their ability to modernize their front-end applications, making any digital transformation or migration to the cloud challenging. The ERP systems were developed with legacy software and architectures which were difficult to maintain and modernize. In addition, the performance suffered, and they were unable to meet their service level agreements. The pandemic further highlighted that the existing digital platform was single-function/siloed, becoming out-of-date, and not capable of handling huge spikes in user traffic. The stark reminder became evident with the significant increase in pool use during lockdown compounded with the closure of popular sales channels like their brick-and-mortar, face-to-face business. As a result, the only channel for purchasing items was the e-commerce platform, and the increased online workload became more difficult to support. The pandemic thus forced them to accelerate their upgrade effort and shorten their implementation window from 2 years down to 8 months.

It was clear from the start that the development of HPD Lendscape would need a solution that was able to continuously process high volumes of data as fast as possible. The solution also needed to be scalable so that it could accommodate all sizes of factoring solutions. Reliability was of course a critical factor and having downtime was not an option. To support their agile teams, the solution needed to be easy to understand, build, and deploy. In addition, the application has evolved to use the Spring Framework as well as other widely adopted frameworks in order to better support the future maintainability of the application. As the market has evolved and adapted to changing technologies, so too has HPD Lendscape’s solution. The most recent evolution has focused on cloud adoption and to this end, HPD Lendscape is able to host on AWS and Azure. Initially, Ehcache was used as the in-memory solution deployed for Lendscape and it has continued to prove sufficient for single-server deployment. However, to provide solutions for the future that allows for scalable multi-node deployment, they needed a caching solution that would support real-time transactions, with very high throughput and low latency and would run continuously without service outages.

The bank was looking to expand their online payments business, but was hampered by the inflexibility of their existing solution. The existing application architecture could not scale up to meet the demand of larger customers that could unlock the highest potential return on their technology investments. In addition, the legacy code was difficult to extend and evolve, so that adding new features or adapting to facilitate entry into new markets could not be done in a timely fashion - release cycles of the monolithic application were generally six months in duration. One of the client banks in Hong Kong had a requirement for a 50x increase in transaction speed, so this became one of the criteria for evaluating the performance of the solution. Even if large investments were made in upgrading the hardware environment for the application, the bank was doubtful that such an improvement would be possible with the existing software architecture.

The business challenge they faced was to increase the adoption of its products to its customer base. The bank’s marketing team identified a set of responses to specific customer situations, which would result in an offer for an upsell/cross-sell product. One straightforward offer would be to promote personal loans to any customer whose bank account balance was low and could not provide the requested amount of cash via an ATM. The “error” notification was captured by the bank, so it was theoretically easy to quickly respond with the right offer to the customer. The marketing team expected that a timelier response would be advantageous for increasing customer conversions, so they turned to the IT team for help. The team had built an elaborate architecture consisting of a services-oriented architecture (SOA) and an enterprise service bus (ESB) that drove data flows across the bank’s operations. All client-facing and back-office applications were linked via the SOA bus. This architecture was the backbone of their IT infrastructure and had been operating very reliably for the bank for several years. Similar to their previous use cases that incorporated Hazelcast, they wanted to retain all of the existing work, and only add components where necessary to add new business capabilities. This was important to ensure they added no major risk of disruption to their existing operations, considering that everything was already working well. However, the batch-oriented infrastructure based on CRM and data warehouse technology meant that it would typically take up to two days to present the customer with an offer. This would not meet the marketing team’s requirements on timely responsiveness.

Users of Whitepages’ people search and identity verification services expect instant results from a single piece of contact information, which requires a highly efficient and fast database system. The company's proprietary Identity Graph™ database, which houses billions of person-identity records, generates a high volume of calls to Redis, especially during peak times. Initially, Whitepages used Amazon ElastiCache to store IDs, but as the company expanded globally, this solution became resource-intensive and unwieldy. The company evaluated MongoDB, Apache Cassandra, and Couchbase as potential replacements, but none could handle the full dataset size while providing the required single-digit latency. Whitepages' applications are extremely latency-sensitive, and customer SLAs promise sub-hundred millisecond latency, leaving no room for error.

In late 2014, Etermax’s online Trivia Crack game went viral, leading to a rapid increase in users. The company faced significant challenges with its existing open source Redis installation, including CPU bottlenecks, memory limitations, and high costs for maintaining a redundant infrastructure. The single-threaded nature of Redis and the inability to utilize all cores of the largest AWS instances further exacerbated the problem. Etermax needed a solution that could handle the high availability and performance demands of its growing user base, which was increasing by two to three million new users every week.

Editoo’s promise to customers is a professional-grade magazine produced in a short amount of time. When customers first visited Editoo’s website, they were met with slow response times and high latency. This was a problem; a fast user interface is crucial to retaining a customer’s attention, especially if speed is part of a company’s mission statement. Below are the challenges that led Editoo to evaluate and ultimately select Redis Enterprise: Encountered the following challenges before choosing Redis Enterprise: High latency and slow response times from other databases.

Udemy faced significant challenges with their previous database solutions, including data loss and downtime. These issues were critical as they impacted the user experience and the company's ability to scale effectively. The difficulty in operating, scaling, and administering other databases led Udemy to seek a more robust solution. The need for a database that could handle real-time analytics, high-speed transactions, and a growing user base was paramount. Additionally, the company required a solution that could support multiple locations and data models, ensuring seamless scalability and high availability.

Scopely, a rapidly growing mobile gaming company, faced several challenges in maintaining stable, top performance for their games. Initially, they used Amazon’s Elasticache for Redis management but found it required unrealistic levels of self-monitoring. High availability and sub-millisecond response times were crucial for their business, as any performance issues could lead to users switching to other applications. Additionally, Scopely needed to consolidate efforts, focusing on technology innovation while outsourcing non-core services to save time and money. With a modest-sized operations team, they did not want to burden their developers with managing Redis. Lastly, scalability was a significant concern. Scopely's games could rapidly grow from thousands to hundreds of thousands of users within 24 hours, necessitating efficient and quick scaling of their Redis databases.

Today, malware threats are everywhere, every day. Anyone who uses computer technology—a smart phone, desktop, laptop, tablet—for business or personal use can be targeted by the “bad guys” of this world. In the last 12 months, dating back to August of 2014, research estimates that more than 350,000,000 pieces of malware have been designed to hack into infrastructures, steal personal information, financial and corporate records, or simply to plant a virus to cause destruction and chaos. All pieces of malware start out as what can be called unknown files. But with this clear onslaught of millions of pieces of malware each year, the traditional blacklisting of files to keep them away from infecting and breaching the walls of technology infrastructures cannot keep up. Additionally, traditional antivirus solutions focus on detection—not prevention—using default allow technology, which only stops recognized, blacklisted files. So when that one unknown file does not make it to the blacklist in time, it’s allowed to pass right through into a computer network, and the next cyber-attack happens. All it takes is one employee to open one email attachment that was allowed to pass through because it was not recognized as a bad file. Scary. And what can make this even scarier is that malware isn’t discriminatory. It attacks enterprises large and small. It attacks the infrastructures of banks, hospitals, and non-profit organizations, causing millions of dollars in damages. For county governments, the risks are the same as large enterprises or the small business: the need to protect and contain their information.

As the Aviva organization added more clients and continued to grow, the organization outgrew its IT infrastructure and needed to add more network and IT capabilities, specifically when it came to the management process around its digital certificates. Aviva no longer had a single location or management system for all of its certificates, thus experiencing higher costs associated with individualized certificates delay in certificate signing request turn-around times for the issuance of new SSL certificates. Aviva was in need of a new management solution for its certificates.

Before implementing the Comodo One MSP IT management platform, XL Pro was servicing its customers through physical, on-site visits. To try and service more customers in less time, XL Pro started investigating purchasing its first RMM solution that would deliver a secure and reliable performance for both its customers and its own workforce –while not adding cumbersome costs.

Fetco Home Decor was experiencing a rampant outbreak of the W32. changeup virus. The virus was extremely persistent in that users were being re-infected whenever they connected to the organization’s file server. The Fetco CFO needed a way to isolate and fix the problem once and for all and prevent future infections from occurring. After being infected with a serious and persistent virus outbreak that the existing antivirus and managed email solutions vendor missed, Fetco Home Decor needed to remediate and proactively protect their corporate environment from future risk. Based on the experience, the Fetco team made the decision for their MSP to remove the existing antivirus software provider and deploy Endpoint Security Manager from Comodo. The unique Default Deny Architecture and patent pending Auto Sandbox Technology would help ensure that this, or any other virus, could not infect the computers of the firm. The existing managed email protection service was also removed and switched to Comodo’s Antispam Gateway service, providing the ability to prevent and filter malicious attachments, virus and malware threats, phishing attacks, and automated spambots, while reducing the overall amount of junk mail.

Ratcliff IT faced the challenge of moving beyond commodity support to offer differentiated expertise and services. The company struggled to build deeper relationships with clients while their top technical minds were occupied with routine tasks like programming RMM tools and reading logs. This situation hindered their ability to add value as a trusted partner. Ratcliff IT needed a solution that would allow them to focus on more strategic activities and build a sustainable, scalable business. They evaluated various management options and found that Continuum Command offered the best service on the market. The goal was to free up their staff from background support tasks so they could concentrate on adding value to their clients.