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Amazon EC2 instances and comparison

Amazon is the market leader in cloud solution and it offers customers a wide range of EC2 instances.
Amazon Elastic Compute Cloud (Amazon EC2) is one of the most widely used services of AWS. This service is used to create and use virtual machines as service.

Most of the time when we require a virtual machine we just for T2 instance type which is meant for the general purpose. But AWS also provides a wide range of EC2 instance types which are meant for specific reasons.

General Purpose instances T2 M5 M4
Compute Optimized C5 C4
Memory Optimized X1e X1 R4
Accelerated Computing P3 P2 G3 F1
Storage Optimized H1 I3 D2

T2

Use Case: Websites and web applications, development environments, build servers, code repositories, microservices, test and staging environments, and line of business applications.

M5

Use Case: Small and mid-size databases, data processing tasks that require additional memory, caching fleets, and for running backend servers for SAP, Microsoft SharePoint, cluster computing, and other enterprise applications.

M4

Use Case: Small and mid-size databases, data processing tasks that require additional memory, caching fleets, and for running backend servers for SAP, Microsoft SharePoint, cluster computing, and other enterprise applications.

C5

Use Case: High-Performance web servers, scientific modeling, batch processing, distributed analytics, high-performance computing (HPC), machine/deep learning inference, ad serving, highly scalable multiplayer gaming, and video encoding.

C4

Use Case: High performance front-end fleets, web-servers, batch processing, distributed analytics, high performance science and engineering applications, ad serving, MMO gaming, and video-encoding.

X1e

Use Case: High-Performance databases, in-memory databases (e.g. SAP HANA) and memory intensive applications. x1e.32xlarge instance certified by SAP to run next-generation Business Suite S/4HANA, Business Suite on HANA (SoH), Business Warehouse on HANA (BW), and Data Mart Solutions on HANA on the AWS cloud.

X1

Use Case: In-memory databases (e.g. SAP HANA), big data processing engines (e.g. Apache Spark or Presto), high performance computing (HPC). Certified by SAP to run Business Warehouse on HANA (BW), Data Mart Solutions on HANA, Business Suite on HANA (SoH), Business Suite S/4HANA.

R4

Use Case: High-Performance databases, data mining & analysis, in-memory databases, distributed web scale in-memory caches, applications performing real-time processing of unstructured big data, Hadoop/Spark clusters, and other enterprise applications.

P3

Use Case: Machine/Deep learning, high performance computing, computational fluid dynamics, computational finance, seismic analysis, speech recognition, autonomous vehicles, drug discovery.

P2

Use Case: Machine learning, high performance databases, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, genomics, rendering, and other server-side GPU compute workloads.

G3

Use Case: 3D visualizations, graphics-intensive remote workstation, 3D rendering, application streaming, video encoding, and other server-side graphics workloads.

F1

Use Case: Genomics research, financial analytics, real-time video processing, big data search and analysis, and security.

H1

Use Case: MapReduce-based workloads, distributed file systems such as HDFS and MapR-FS, network file systems, log or data processing applications such as Apache Kafka, and big data workload clusters.

I3

Use Case: NoSQL databases (e.g. Cassandra, MongoDB, Redis), in-memory databases (e.g. Aerospike), scale-out transactional databases, data warehousing, Elasticsearch, analytics workloads.

D3

Use Case: Massively Parallel Processing (MPP) data warehousing, MapReduce and Hadoop distributed computing, distributed file systems, network file systems, log or data-processing applications

Mantra Labs is the technical partner with AWS to help our customers of all sizes design, architect, build, migrate, and manage their workloads and applications on AWS.

For more information, please write us at hello@mantralabsglobal.com

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Retention playbook for Insurance firms in the backdrop of financial crises

4 minutes read

Belonging to one of the oldest industries in the world, Insurance companies have weathered multiple calamities over the years and have proven themselves to be resilient entities that can truly stand the test of time. Today, however, the industry faces some of its toughest trials yet. Technology has fundamentally changed what it means to be an insurer and the cumulative effects of the pandemic coupled with a weak global economic output have impacted the industry in ways both good and bad.

Chart, line chart

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Source: Deloitte Services LP Economic Analysis

For instance, the U.S market recorded a sharp dip in GDP in the wake of the pandemic and it was expected that the economy would bounce back bringing with it a resurgent demand for all products (including insurance) across the board. It must be noted that the outlook toward insurance products changed as a result of the pandemic. Life insurance products were no longer an afterthought, although profitability in this segment declined over the years. Property-and-Casualty (P&C) insurance, especially motor insurance, continued to be a strong driver, while health insurance proved to be the fastest-growing segment with robust demand from different geographies

Simultaneously, the insurance industry finds itself on the cusp of an industry-wide shift as technology is starting to play a greater role in core operations. In particular, technologies such as AI, AR, and VR are being deployed extensively to retain customers amidst this technological and economic upheaval.

Double down on digital

For insurance firms, IT budgets were almost exclusively dedicated to maintaining legacy systems, but with the rise of InsurTech, it is imperative that firms start dedicating more of their budgets towards developing advanced capabilities such as predictive analytics, AI-driven offerings, etc. Insurance has long been an industry that makes extensive use of complex statistical and mathematical models to guide pricing and product development strategies. By incorporating the latest technological advances with the rich data they have accumulated over the years, insurance firms are poised to emerge stronger and more competitive than ever.

Using AI to curate a bespoke customer experience

Insurance has always been a low-margin affair and success in the business is primarily a function of selling the right products to the right people and reducing churn as much as possible. This is particularly important as customer retention is normally conceived as an afterthought in most industries, as evidenced in the following chart.

Chart, sunburst chart

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        Source: econconusltancy.com

AI-powered tools (even with narrow capabilities) can do wonders for the insurance industry at large. When architected in the right manner, they can be used to automate a bulk of the standardized and automated processes that insurance companies have. AI can be used to automate and accelerate claims, assess homeowner policies via drones, and facilitate richer customer experiences through sophisticated chatbots. Such advances have a domino effect of increasing CSAT scores, boosting retention rates, reducing CACs, and ultimately improving profitability by as much as 95%.

Crafting immersive products through AR/VR

Customer retention is largely a function of how good a product is, and how effective it is in solving the customers’ pain points. In the face of increasing commodification, insurance companies that go the extra mile to make the buying process more immersive and engaging can gain a definite edge over competitors.

Globally, companies are flocking to implement AR/VR into their customer engagement strategies as it allows them to better several aspects of the customer journey in one fell swoop. Relationship building, product visualization, and highly personalized products are some of the benefits that AR/VR confers to its wielders.  

By honoring the customer sentiments of today and applying a slick AR/VR-powered veneer over its existing product layer, insurance companies can cater to a younger audience (Gen Z) by educating them about insurance products and tailoring digital delivery experiences. This could pay off in the long run by building a large customer base that could be retained and served for a much longer period.

The way forward

The Insurance industry is undergoing a shift of tectonic proportions as an older generation makes way for a new and younger one that has little to no perceptions about the industry. By investing in next-generation technologies such as AR/VR, firms can build new products to capture this new market and catapult themselves to leadership positions simply by way of keeping up with the times.

We have already seen how AR is a potential game-changer for the insurance industry. It is only a matter of time before it becomes commonplace.

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