The thesis deals with selection of infrastructure virtualization platform focusing on containerization with sandboxing support and with following examination of its difculty. The work begins with an explanation of the basic technologies such as: virtualization, cloud computing and containerization, along with their representatives, that mediate the technology. A special scope is defned for cloud computing platforms: Kubernetes, OpenStack and OpenShift. Futhermore, the most suitable platform is selected and deployed using own technique so that it fullflls all the conditions specifed by thesis supervisor. Within the difculty testing of the selected platform, there are created scripts (mainly in the Bash language) for scanning system load, creating scenarios, stress testing and automation.

Företag som är intresserade av att gå över från ett traditionellttillvägagångssätt att driftsätta sin applikationsmiljö i en mer moderncontainerbaserad miljö saknas ofta den kunskap och erfarenhet som behövs.Det här arbetet syftar till att ge förslag till företag kring hur de bör gå tillvägaför att flytta sin nuvarande traditionella infrastrukturella lösning, vare sig detär fysiska eller virtuella servrar, till en containerbaserad lösning. Projektetsyftar också till att ge företag som är intresserade av en sådan migration enteoretisk grund att stå på för att undvika att gå i de fällor som är vanliga att gåi. Resultatet baseras på en litteraturstudie som i sin tur resulterade i ensammanfattning över vad som bör ingå i en migrationsstrategi samt ett antalpraktiskt tillämpningsbara beslutsträd.

The accelerating progress in network speeds and computing power permitted the architectural design paradigm to shift from monolithic applications to microservices. The industry moved from single-core and multi-threads, code-heavy applications, running on giant machines 24/7 to smaller machines, multi-cores single threads where computing power and memory consumption are managed very critically. With the advent of this novel approach to designing systems, traditional multi-tier applications have been broken down into hundreds of microservices that can be easily moved around, start, and stop quickly. In this context, scaling assumed a new meaning, rather than scaling up by adding more resources or computing power, now systems are scaled dynamically by adding more microservices instances. This contribution proposes a theoretical study and a practical experiment to investigate, compare and outline the performance improvements aid by the implementation of Protocol Buffers, Google's language-neutral, binary-based representational data interchange format over traditional text-based serialization formats in a modern, Cloud-Native, REST-based Java Microservice architecture. Findings are presented showing promising results regarding the implementation of Protobuf, with a significant reduction in response time (25.1% faster in the best-case scenario) and smaller payload size (72.28% better in the best-case scenario) when compared to traditional textual serialization formats while literature revealed out-of-the-box mechanisms for message versioning with backward compatibility.

With the exponential growth of virtualization and cloud computing over the last decade, many companies in the telecommunications sector have started their journey towards cloud migration by exchanging a lot of specialized hardware for virtualized solutions. With more and more applications running in a cloud environment, it became essential to run these applications on heterogeneous systems with shared underlying hardware and software resources. However, running these applications in a heterogeneous cloud environment often leads to  unpredictable and non-deterministic performance, as all the applications compete for the shared resources to improve their individual performance. This becomes a problem when the interference from the co-hosted applications starts affecting the performance of the critical applications running on the same server. Ericsson is therefore investigating a solution to dynamically manage the low-level hardware and software resources to get deterministic performance on applications deployed using Kubernetes.  In this thesis, the Intent Driven Orchestration (IDO) model developed by Intel is used as the baseline model. This model was then extended by adding another tool to the setup called Container Runtime Interface-Resource Manager (CRI-RM), which is used to manipulate low-level software and hardware resources managed by a Kubernetes cluster at runtime. The results achieved in this thesis suggest that it is possible to get deterministic performance for an application deployed using Kubernetes, by identifying and isolating the CPU cores in the cluster on which the application is running.

The growth of distributed applications stand on a foundation of containers and their communication and have seen the rise and fall of many implementations throughout the years with a mix of proprietary and open sources. Today there are two implementations widely used as a result of the popularity of the huge project Kubernetes: CRI-O and Containerd. Both with the edge responsibility of managing containers using similar underlying software raising the question; do they have any implications on the containers they spawn? This thesis investigate these implementations from a performance perspective with a custom developed tool for direct communication to them and run a suite of benchmarks within the containers created by each. The suite consists of tests for throughput, latency, cpu, memory, random file read/write and sequential file read/write. Results conclude they perform similarly in all, but the file tests which showed overall CRI-O dominating in write speed and Containerd dominating the read speed.

Due to the growing complexity of systems and high demands on availability, fault tolerance, and scalability, more stateful applications are being moved to Kubernetes. There are two problems associated with this: (1) At the moment, there is a lack of industry standards when it comes to what is essential in a lifecycle management framework for stateful applications on top of Kubernetes. (2) Due to inadequate knowledge of the existing frameworks in the area and a lack of comparisons between them, there is no consensus on which framework to use. To solve these problems, this study reviews the field for existing frameworks and then evaluates the framework based on a set of metrics. The frameworks chosen for comparison during the study are (1) Operator Framework, (2) Shell Operator, (3) Kopf, and (4) KUDO. When comparing the frameworks, it becomes apparent that Operator Framework should be used in most cases. Kopf or Shell Operator can be used when creating simple scheduled activities or when the developing team is very knowledgeable in Python or Bash.

The usage of cloud computing in order to move away from local servers and infrastructure have grown enormously the last decade. The ability to quickly scale capacity of servers and their resources at once when needed is something that can both be a price saver for companies and help them deliver high end products that will function correctly at all times even under heavy load to their customers. To meet todays challenges, one of the strategic directions of Attentec, a software company located in Linköping, is to examine the world of cloud computing in order to deliver robust and scalable applications to their customers. This thesis investigates the usage of cloud services in order to deploy scalable applications which can adapt to usage peaks within minutes.

No description available.

The purpose of this thesis paper was to develop new features in the cloud-native and open-source machine learning platform STACKn, aiming to strengthen the platform's support for conducting reproducible machine learning experiments through provenance, transparency and reusability. Adhering to the definition of reproducibility as the ability of independent researchers to exactly duplicate scientific results with the same material as in the original experiment, two concepts were explored as alternatives for this specific goal: 1) Increased support for standardized textual documentation of machine learning models and their corresponding datasets; and 2) Increased support for provenance to track the lineage of machine learning models by making code, data and metadata readily available and stored for future reference. We set out to investigate to what degree these features could increase reproducibility in STACKn, both when used in isolation and when combined.  When these features had been implemented through an exhaustive software engineering process, an evaluation of the implemented features was conducted to quantify the degree of reproducibility that STACKn supports. The evaluation showed that the implemented features, especially provenance features, substantially increase the possibilities to conduct reproducible experiments in STACKn, as opposed to when none of the developed features are used. While the employed evaluation method was not entirely objective, these features are clearly a good first initiative in meeting current recommendations and guidelines on how computational science can be made reproducible.

Mobilné zariadenia sú v rámci technologickej histórie novinka a pri technológii, ktorá sa vyvíja tak rapídnym tempom a rastom používania je nutné dbať na zabezpečenie. Táto diplomová práca sa zaoberá rozborom bezpečnostných mechanizmov používaných v Android OS a komunikáciou medzi OS Android a vzdialeným serverom. Cieľom je preskúmať tieto mechanizmy a otestovať aké kryptografické metódy a postupy je najvýhodnejšie používať z hľadiska bezpečnosti s ohľadom na efektivitu. Tieto znalosti boli použité pre vytvorenie demonštračného systému, ktorý využíva vybrané zabezpečovacie mechanizmy a kryptografické postupy.